An Application of a Multi-Tier Data Warehouse in Oil and Gas Drilling Information Management

Expenditure on wells constitute a significant part of the operational costs for a petroleum enterprise, where most of the cost results from drilling. This has prompted drilling departments to continuously look for ways to reduce their drilling costs and be as efficient as possible. A system called the Drilling Comprehensive Information Management and Application System (DCIMAS) is developed and presented here, with an aim at collecting, storing and making full use of the valuable well data and information relating to all drilling activities and operations. The DCIMAS comprises three main parts, including a data collection and transmission system, a data warehouse (DW) management system, and an integrated platform of core applications. With the support of the application platform, the DW management system is introduced, whereby the operation data are captured at well sites and transmitted electronically to a data warehouse via transmission equipment and ETL (extract, transformation and load) tools. With the high quality of the data guaranteed, our central task is to make the best use of the operation data and information for drilling analysis and to provide further information to guide later production stages. Applications have been developed and integrated on a uniform platform to interface directly with different layers of the multi-tier DW. Now, engineers in every department spend less time on data handling and more time on applying technology in their real work with the system.

Multi-Tier数据库应用程序及在Delphi中的实现

介绍了多层数据库应用程序的基本原理及其在Delphi中的实现技术,并以其在学分制教务管理系统开发的程序为原型,通过实例讲述在Delphi中实现Multi-Tier技术的步骤和要点。

使用Multi-Tier技术架构Web应用系统

Web系统目前被广泛应用于Internet/Intranet,随着网络的发展,传统的CGI/ISAPI标准结构已不能满足需要,本文介绍了Delphi的InternetExpress和DatabasePooling等Multi Tier技术,通过对CGI/ISAPI结构与InternetExpress结构的比较,介绍使用InternetExpress技术结合MST(MicrosoftTransactionServer)构建基于Web的三层结构系统的架构过程。并以开发实例加以说明。

Delphi中Multi-Tier结构的应用浅析

Multi Tier结构是目前分布式系统的主要应用结构,本文首先对传统的Two Tier结构数据库和Multi Tier结构数据库系统进行了比较,然后以三层数据库应用系统为例介绍Multi Tier结构应用的构建过程,并以一个实例加以说明。

Storage Assignment Optimization in a Multi-tier Shuttle Warehousing System

The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retrieval system（AS/RS）.However,the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems（MSWS） because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP.In this study,a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period（SWP） and lift idle period（LIP） during transaction cycle time.A mean arrival time difference matrix for pairwise stock keeping units（SKUs） is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation.The decomposition method is applied to analyze the interactions among outbound task time,SWP,and LIP.The ant colony clustering algorithm is designed to determine storage partitions using clustering items.In addition,goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane.This combination is derived based on the analysis results of the queuing network model and on three basic principles.The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry.The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.

Seismic assessment of two multi-tiered pagodas damaged by the 2015 Nepal earthquake

A seismic assessment of two multi-tier pagodas by numerical analysis is presented herein.The Changu Narayan temple and the Kumbeshwar temple in Nepal are used as the case studies.Both pagodas are built of brick masonry in earthen mortar,with timber columns and crossbeams.The Changu Narayan temple is a two-tier pagoda,and was seriously damaged during the 2015 Gorkha earthquake.The Kumbeshwar temple is a five-tier pagoda,and its top-tier collapsed due to the Gorkha earthquake.A seismic assessment was carried out using finite element(FE)analysis.The FE models were prepared,and dynamic identification tests and penetrometer tests were conducted.Pushover analysis and nonlinear dynamic analysis were performed as part of the seismic assessment.The main shock of the 2015 Gorkha earthquake was considered as the input accelerograms.The behavior between the two pagodas was compared with the collapse mechanisms and damage patterns observed in the actual structures.The comparison suggested common structural features of multi-tier pagodas.This study is dedicated to providing a better understanding of the seismic behavior of multi-tier pagoda-type structures and provides suggestions for their effective analysis.

Delphi与Multi-tiered应用开发

概述了数据库应用技术的发展历程。介绍了三层应用的结构及优点。以开发工具Delphi为例阐述了三层应用的工作原理与开发。

Performance Evaluation Approach for Multi-Tier Cloud Applications

Complex multi-tier applications deployed in cloud computing environments can experience rapid changes in their workloads. To ensure market readiness of such applications, adequate resources need to be provisioned so that the applications can meet the demands of specified workload levels and at the same time ensure that service level agreements are met. Multi-tier cloud applications can have complex deployment configurations with load balancers, web servers, application servers and database servers. Complex dependencies may exist between servers in various tiers. To support provisioning and capacity planning decisions, performance testing approaches with synthetic workloads are used. Accuracy of a performance testing approach is determined by how closely the generated synthetic workloads mimic the realistic workloads. Since multi-tier applications can have varied deployment configurations and characteristic workloads, there is a need for a generic performance testing methodology that allows accurately modeling the performance of applications. We propose a methodology for performance testing of complex multi-tier applications. The workloads of multi-tier cloud applications are captured in two different models-benchmark application and workload models. An architecture model captures the deployment configurations of multi-tier applications. We propose a rapid deployment prototyping methodology that can help in choosing the best and most cost effective deployments for multi-tier applications that meet the specified performance requirements. We also describe a system bottleneck detection approach based on experimental evaluation of multi-tier applications.

基于Delphi的Multi-Tier C/S结构数据库应用程序的设计

Delphi是当今开发C/S结构数据库应用系统的主流工具之一。基于Two-Tier C/S结构存在的问题.本文提出了Multi-Tier C/S结构的开发模式,并就Delphi的Multi-Tier C/S结构数据库应用程序设计原理、优越性进行深入探讨,最后简单介绍了Delphi的Multi-Tier C/S结构数据库应用程序创建方法。

Data Temperature Informed Streaming for Optimising Large-Scale Multi-Tiered Storage

Data temperature is a response to the ever-growing amount of data.These data have to be stored,but they have been observed that only a small portion of the data are accessed more frequently at any one time.This leads to the concept of hot and cold data.Cold data can be migrated away from high-performance nodes to free up performance for higher priority data.Existing studies classify hot and cold data primarily on the basis of data age and usage frequency.We present this as a limitation in the current implementation of data temperature.This is due to the fact that age automatically assumes that all new data have priority and that usage is purely reactive.We propose new variables and conditions that influence smarter decision-making on what are hot or cold data and allow greater user control over data location and their movement.We identify new metadata variables and user-defined variables to extend the current data temperature value.We further establish rules and conditions for limiting unnecessary movement of the data,which helps to prevent wasted input output(I/O)costs.We also propose a hybrid algorithm that combines existing variables and new variables and conditions into a single data temperature.The proposed system provides higher accuracy,increases performance,and gives greater user control for optimal positioning of data within multi-tiered storage solutions.

More Requests, Less Cost： Uncertain Inter-Datacenter Traffic Transmission with Multi-Tier Pricing

With the multi-tier pricing scheme provided by most of the cloud service providers （CSPs）, the cloud userstypically select a high enough transmission service level to ensure the quality of service （QoS）, due to the severe penalty ofmissing the transmission deadline. This leads to the so-called over-provisioning problem, which increases the transmissioncost of the cloud user. Given the fact that cloud users may not be aware of their traffic demand before accessing the network,the over-provisioning problem becomes more serious. In this paper, we investigate how to reduce the transmission cost fromthe perspective of cloud users, especially when they are not aware of their traffic demand before the transmission deadline.The key idea is to split a long-term transmission request into several short ones. By selecting the most suitable transmissionservice level for each short-term request, a cost-efiqcient inter-datacenter transmission service level selection framework isobtained. We further formulate the transmission service level selection problem as a linear programming problem andresolve it in an on-line style with Lyapunov optimization. We evaluate the proposed approach with real traffic data. Theexperimental results show that our method can reduce the transmission cost by up to 65.04%.

Research on resource allocation for multi-tier web applications in a virtualization environment

Resource allocation for multi-tier web appli- cations in virtualization environments is one of the most important problems in autonomous computing. On one hand, the more resources that are provisioned to a multi- tier web application, the easier it is to meet service level objectives （SLO）. On the other hand, the virtual machine which hosts the multi-tier web application needs to be consolidated as much as possible in order to maintain high resource utilization. This paper presents an adaptive resource controller which consists of a feedback utiliza- tion controller and an auto-regressive and moving average model （ARMA）-based model estimator. It can meet application-level quality of service （QoS） goals while achieving high resource utilization. To evaluate the proposed controllers, simulations are performed on a testbed simulating a virtual data center using Xen virtual machines. Experimental results indicate that the control- lers can improve CPU utilization and make the best trade- off between resource utilization and performance for multi-tier web applications.

福建地区不同栽培模式下百香果的产量与品质特征

为探究多级结果蔓栽培模式和单级结果蔓栽培模式下百香果大田生长时间、产量与品质相关指标表现特征,于2020—2021年开展百香果大田生产试验,并以紫果类主栽品种台农1号百香果和黄果类品种芭乐味百香果为材料,观察或测定2种栽培模式下百香果开花、结果、产量与品质相关指标,并分析果实品质指标间,以及果实品质指标与果实成熟期内温度、光照等气象因子的相关性。结果表明:1)与多级结果蔓栽培模式相比,单级结果蔓栽培模式下,百香果植株现蕾期、始花期和始果期的时间均较迟,果实发育成熟所需时间缩短,成花率和坐果率显著增加,且花蕾期、成花率、果实发育成熟期和坐果率的变异系数均较低,台农1号和芭乐味从定植到采收结束时所需时间分别比多级结果蔓栽培模式缩短69~71 d和51~58 d;2)从实收总产量及其产量构成因素看,单级结果蔓栽培模式下单株产量显著低于多级结果蔓栽培模式,且其全部由一级蔓产量组成,而多级结果蔓栽培模式下单株产量由主蔓、一级蔓、二级蔓和三级蔓产量组成,各级结果蔓产量在总产量占比上表现不一致;与多级结果蔓栽培模式相比,单级结果蔓栽培模式下百香果单株结果数量显著减少,但平均单果重和中大果比率显著提高;3)与多级结果蔓栽培模式相比,在单级结果蔓栽培模式下,果实总酸含量显著降低,果皮重、果汁量、可食率、总糖、糖酸比提高,且果实品质中7项指标值的变异系数均较低,温度、光照等气象因子与果实品质存在极显著相关性。综上所述,百香果在单级结果蔓栽培模式下可缩短大田生长时间,而且开花、结果、产量与品质相关指标表现特征均优于多级结果蔓栽培模式,各项指标值变异系数相对稳定。

美国融合教育多层级支持系统的实践:框架、成效与启示

推进融合教育高质量发展是全球教育治理的政策焦点与实践主题。近年来,美国将多层级支持系统作为学校教育支持系统改革的抓手,认为这样可以解决专业支持有限、课堂融入困难与系统排斥等问题。多层级支持系统以生态系统理论为指引,以科学循证实践为基石,以多元赋权文化为标尺,澄清了高质量融合教育发展的逻辑架构、运行机制和组织保障,但受制于美国的政治制度体系和社会文化背景,并未充分发挥其应有的效力。我国应批判性地吸收其经验教训,坚持道路自信与实践创新,完善面向全体学生的适宜融合资源保障机制,构筑数据驱动的个性学习资源支持体系,形成多元主体协作参与的资源整合格局。

高速公路-航空多层复杂货运网络拓扑性质研究

为提高我国交通运输系统运行的效率,应用复杂网络理论,选取2021年货邮吞吐量排名前30的机场所在城市与38个地级市的高速公路数据为研究对象,构建了高速公路-航空多层复杂货运网络。针对高速公路-航空多层复杂货运网络的拓扑性质进行研究。研究结果表明:高速公路-航空多层货运网络具有小世界特性,不具备无标度特性;多层网络中心性分布不均衡,大多城市节点更倾向于连接发达城市;多层网络整体呈现同配程度较低的同配网络,加强区域性联运建设有利于提高联运效率。

基于主从博弈的综合能源系统多能定价及调度优化

双碳目标背景下,针对综合能源系统中的低碳调度问题,提出基于主从博弈的园区电-热综合能源系统多能定价及调度优化策略。首先,介绍了园区运营商与用户的交易模式;其次,建立了主从博弈模型,将园区运营商作为领导者,园区内用户负荷作为跟随者,在园区运营商模型中引入阶梯型碳交易机制,用户负荷模型考虑了用户电热需求响应。最后,采用BAS-PSO(天牛须改进粒子群)算法和CPLEX求解器求解园区运营商定价策略及用户用能策略。仿真结果表明,所提出的优化策略能有效权衡各方利益,实现用户侧负荷峰谷差的下降和碳排放量的减少。

探索创业孵化器的商业模式:一个多层级框架

伴随着知识经济的快速发展,创业孵化器逐步发生进化与演变,其商业价值创造机理已经不同于以往。揭示创业孵化器商业模式的本质特征以及探索其随着时间推移发生演变的规律具有一定理论意义。首先采用扎根理论研究方法,利用NVivo11等软件对数据进行编码以及理论饱和度检验,得到其商业模式基本框架,包含价值主张、价值生产、价值获取三个维度。在此基础上,进一步运用多案例对比研究方法,探索创业孵化器的价值创造规律,并揭示创业孵化器商业模式的进化与演变方向,最终构建了一个多层级理论框架。研究发现:第一,创业孵化器不仅是初创企业的一种有形安排,更是将“知识的服务纳入其价值主张”的有效组织;第二,创业孵化器主要通过有形、无形和网络服务产生价值,这一过程以追求学习效应和合法性为主要目的;第三,创业孵化器最终需要通过佣金、支持服务收费和企业附加值的获取来保证利益,但持久的收益依赖更低的成本结构;第四,创业孵化器商业模式存在一个内在的反馈与进化过程,并最终体现在价值主张的明确化上。对于加强创业孵化器理论体系建设,以及明确创业孵化器商业模式定位、演变方向和衍生逻辑提供了理论与实践启示。

星载轻量化区块链边缘节点多级安全架构设计

在卫星节点上构建区块链系统可有效消除星载数据协同的地域限制,同时减少数据泄露的风险,为卫星互联网提供信任机制的保障。针对区块链和卫星互联网深度融合时存在的网络拓扑高动态、计算资源和链路资源受限、存在蓄意攻击与破坏等问题,基于TrustZone构建了星载区块链边缘节点的多级安全架构,可有针对性地提高星载区块链边缘节点的物理节点、信息系统和可信数据的多级安全性,并在多级安全架构下从星载区块链边缘节点的计算、存储、传输和密码等方面开展了轻量化设计,进而通过星载区块链边缘节点多级安全模拟实验、轻量化设计效果对比分析和数据可信协同模拟实验验证了所提架构的有效性,可为下一步开展基于星载区块链边缘节点的卫星互联网数据应用研究提供技术参考。

分时电价下含电动汽车的微电网群双层多目标优化调度

为解决大规模电动汽车无序充电导致电网出现“峰上加峰”现象,依据电动汽车充电地点的不同将配电网划分为居民区、办公区、商业区微电网,提出基于峰谷差、分时电价、用户充电满意度多目标下的电动汽车充电模式,建立了微电网内运营商峰谷差最小—用户充电费用最少和充电满意度最大的双盈多目标优化调度模型,采用上海市实际居民办公商业混合体,基于MATLAB/NSGA⁃Ⅱ算法求解负荷整形度;采取粒子群优化算法求解电动汽车车主达到充电最优满意度;实现对电动汽车充电时刻和充电功率的引导。实际算例仿真结果表明,该方法能有效降低配电网负荷峰谷差,提高电动汽车充电效率,满足用户充电需求。

我国多层次资本市场资源配置效率测度——基于不同层次的视角

测度我国多层次资本市场各层次的资源配置效率并探究其影响因素。研究发现:(1)在金融危机前,中小板的价格有效性水平在多数情况下围绕主板上下波动并逐渐趋于一致,创业板在设立初期的价格有效性低于主板和中小板,其后创业板的预测性价格有效性(FPE)超过其他两板;(2)主板资源配置效率的下降趋势主要集中在中小板与创业板设立初期;(3)主板FPE在创业板设立前低于中小板,设立后趋于一致,而创业板FPE高于主板和中小板,且揭示性价格有效性(RPE)的层次差异不大,创业板资源配置效率最高、中小板次之、主板最低;(4)部分股权结构特征会影响各层次的资源配置效率。