Evolutionary-assisted reinforcement learning for reservoir real-time production optimization under uncertainty

Production optimization has gained increasing attention from the smart oilfield community because it can increase economic benefits and oil recovery substantially.While existing methods could produce high-optimality results,they cannot be applied to real-time optimization for large-scale reservoirs due to high computational demands.In addition,most methods generally assume that the reservoir model is deterministic and ignore the uncertainty of the subsurface environment,making the obtained scheme unreliable for practical deployment.In this work,an efficient and robust method,namely evolutionaryassisted reinforcement learning(EARL),is proposed to achieve real-time production optimization under uncertainty.Specifically,the production optimization problem is modeled as a Markov decision process in which a reinforcement learning agent interacts with the reservoir simulator to train a control policy that maximizes the specified goals.To deal with the problems of brittle convergence properties and lack of efficient exploration strategies of reinforcement learning approaches,a population-based evolutionary algorithm is introduced to assist the training of agents,which provides diverse exploration experiences and promotes stability and robustness due to its inherent redundancy.Compared with prior methods that only optimize a solution for a particular scenario,the proposed approach trains a policy that can adapt to uncertain environments and make real-time decisions to cope with unknown changes.The trained policy,represented by a deep convolutional neural network,can adaptively adjust the well controls based on different reservoir states.Simulation results on two reservoir models show that the proposed approach not only outperforms the RL and EA methods in terms of optimization efficiency but also has strong robustness and real-time decision capacity.

An Efficient Crash Recovery Technique for Real-Time Main Memory Database

This paper presents an efficient recovery scheme suitable for real-time mainmemory database. In the recovery scheme, log records are stored in non-volatile RAM which is dividedinto four different partitions based on transaction types. Similarly, a main memory database isdivided into four partitions based data types. When the using ratio of log store area exceeds thethreshold value, checkpoint procedure is triggered. During executing checkpoint procedure, someuseless log records are deleted. During restart recovery after a crash, partition reloading policyis adopted to assure that critical data are reloaded and restored in advance, so that the databasesystem can be brought up before the entire database is reloaded into main memory. Therefore downtime is obvionsly reduced. Simulation experiments show our recovery scheme obviously improves thesystem performance, and does a favor to meet the dtadlints of real-time transactions.

Designing and Realization of Database Platform of County Agricultural Production Technology in Yunnan Province

According to the objective reality in Yunnan Province,such as great difference of weather,a great proportion of minorities,technological backwardness of agricultural production,low conversion rate of research accomplishments,and a limited number of agricultural technical personnel,ASP.NET technique and SQL Server 2005 database technique are adopted.Database platform of county agricultural production technology in Yunnan Province is established by using B/S structure.This platform includes presentation layer,application layer,and data layer,involving regional information,technology column information,technology classification information,technology content and other databases.It has six functional modules,namely information browse,system management,regional maintenance,technical section maintenance,category maintenance and technical information release,integrating crop cultivation,livestock breeding,economic forest management,plant protection,agricultural products processing,agricultural machinery use and other agricultural technical information.This platform can exchange information dynamically with the client,perform the query request from users,and send the result to users.This database platform has friendly interface,profuse information,high pertinency and so on,which offers rich and reliable information resources to farmers,agricultural technical personnel,and government.At present,this platform has been popularized in some areas of Yunnan Province and has obtained good results.

Scheduling transactions in mobile distributed real-time database systems

A DMVOCC-MVDA （distributed multiversion optimistic concurrency control with multiversion dynamic adjustment） protocol was presented to process mobile distributed real-time transaction in mobile broadcast environments. At the mobile hosts, all transactions perform local pre-validation. The local pre-validation process is carried out against the committed transactions at the server in the last broadcast cycle. Transactions that survive in local pre-validation must be submitted to the server for local final validation. The new protocol eliminates conflicts between mobile read-only and mobile update transactions, and resolves data conflicts flexibly by using multiversion dynamic adjustment of serialization order to avoid unnecessary restarts of transactions. Mobile read-only transactions can be committed with no-blocking, and respond time of mobile read-only transactions is greatly shortened. The tolerance of mobile transactions of disconnections from the broadcast channel is increased. In global validation mobile distributed transactions have to do check to ensure distributed serializability in all participants. The simulation results show that the new concurrency control protocol proposed offers better performance than other protocols in terms of miss rate, restart rate, commit rate. Under high work load （think time is ls） the miss rate of DMVOCC-MVDA is only 14.6%, is significantly lower than that of other protocols. The restart rate of DMVOCC-MVDA is only 32.3%, showing that DMVOCC-MVDA can effectively reduce the restart rate of mobile transactions. And the commit rate of DMVOCC-MVDA is up to 61.2%, which is obviously higher than that of other protocols.

Validation concurrency control protocol in parallel real-time database systems

In parallel real-time database systems, concurrency control protocols must satisfy time constraints as well as the integrity constraints. The authors present a validation concurrency control(VCC) protocol, which can enhance the performance of real-time concurrency control mechanism by reducing the number of transactions that might miss their deadlines, and compare the performance of validation concurrency control protocol with that of HP2PL(High priority two phase locking) protocol and OCC-TI-WAIT-50(Optimistic concurrency control-time interval-wait-50) protocol under shared-disk architecture by simulation. The simulation results reveal that the protocol the author presented can effectively reduce the number of transactions restarting which might miss their deadlines and performs better than HP2PL and OCC-TI-WAIT-50. It works well when arrival rate of transaction is lesser than threshold. However, due to resource contention the percentage of missing deadline increases sharply when arrival rate is greater than the threshold.

A dynamic crash recovery scheme for distributed real-time database systems

Recovery performance in the event of failures is very important for distributed real-time database systems. This paper presents a time-cognizant logging-based crash recovery scheme （TCLCRS） that aims at distributed real-time databases, which adopts a main memory database as its ground support. In our scheme, each site maintains a real-time log for local transactions and the subtransactions, which execute at the site, and execte local checkpointing independently. Log records are stored in non-volatile high- speed store, which is divided into four different partitions based on transaction classes. During restart recovery after a site crash, partitioned crash recovery strategy is adopted to ensure that the site can be brought up before the entire local secondary database is reloaded in main memory. The partitioned crash recovery strategy not only guarantees the internal consistency to be recovered, but also guarantee the temporal consistency and recovery of the sates of physical world influenced by uncommitted transactions. Combined with two- phase commit protocol, TCLCRS can guarantee failure atomicity of distributed real-time transactions.

Quasi Serializable Concurrency Control in Distributed Real-Time Database Systems

This paper formally defines and analyses the new notion of correctness called quasi serializability, and then outlines corresponding concurrency control protocol QDHP for distributed real-time databases. Finally, through a series of simulation studies, it shows that using the new concurrency control protocol the performance of distributed real-time databases can be much improved.

A new product family mining method based on PLM database

Product family(PF) is the most important part of product platform. A new method is proposed to mine PF based on multi-space product data in PLM database. Product structure tree(PST) and bill of material(BOM) are used as the data source. A PF can be obtained by mining physics space, logic space and attribute space of product data. In this work, firstly, a PLM database is described, consisting of data organization form, data structure, and data characteristics. Then the PF mining method introduces the sequence alignment techniques used in bio-informatics, which mainly includes data pre-processing, regularization, mining algorithm and cluster analysis. Finally, the feasibility and effectiveness of the proposed method are verified by a case study of high and middle pressure valve, demonstrating a feasible method to obtain PF from PLM database.

Real-Time Memory Data Optimization Mechanism of Edge IoT Agent

With the full development of disk-resident databases(DRDB)in recent years,it is widely used in business and transactional applications.In long-term use,some problems of disk databases are gradually exposed.For applications with high real-time requirements,the performance of using disk database is not satisfactory.In the context of the booming development of the Internet of things,domestic real-time databases have also gradually developed.Still,most of them only support the storage,processing,and analysis of data values with fewer data types,which can not fully meet the current industrial process control system data types,complex sources,fast update speed,and other needs.Facing the business needs of efficient data collection and storage of the Internet of things,this paper optimizes the transaction processing efficiency and data storage performance of the memory database,constructs a lightweight real-time memory database transaction processing and data storage model,realizes a lightweight real-time memory database transaction processing and data storage model,and improves the reliability and efficiency of the database.Through simulation,we proved that the cache hit rate of the cache replacement algorithm proposed in this paper is higher than the traditional LRU(Least Recently Used)algorithm.Using the cache replacement algorithm proposed in this paper can improve the performance of the system cache.

A product module mining method for PLM database

Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in enterprises, the product lifecycle data have been effectively managed. However, these data have not been fully utilized in module division, especially for complex machinery products. To solve this problem, a product module mining method for the PLM database is proposed to improve the effect of module division. Firstly, product data are extracted from the PLM database by data extraction algorithm. Then, data normalization and structure logical inspection are used to preprocess the extracted defective data. The preprocessed product data are analyzed and expressed in a matrix for module mining. Finally, the fuzzy c-means clustering(FCM) algorithm is used to generate product modules, which are stored in product module library after module marking and post-processing. The feasibility and effectiveness of the proposed method are verified by a case study of high pressure valve.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.

A Domain Engineering Approach to Increase Productivity in the Development of a Service for Changes Notification of the Configuration Management Database

This paper presents a domain engineering approach to build a software product line that supports the change notification service in a Configuration Management Database (CMDB) according to the Information Technology Infrastructure Library (ITIL) best practices. For the development of this product line, the proposed approach makes use of a construction of products methodology by analogy: this is a new notation which reports the variability of the products, obtaining metrics as important as the number of products and uses a language that enables, by means of the flexibilization of a product and the development of some generators, to build the rest of the product line. In addition the paper offers a standard for the analysis and design of the CMDB as well. Finally, the paper presents an economic model for the product line, where the profitability and productivity of the proposed solution are analyzed.

Comparison of Two Real-time PCR Technigues for Quantification of GMO Contents in Highly Processed Products of Soybean

The RR soybean was quantitatively detected by ABI Prism 7300 sequence detector with PCR primers and fluorescence probes were designed according to the sequences of endogenous Lectin gene and exogenous CP4-EPSPS gene, and the PCR systems were based on SYBR Green I and TaqMan. The standard curve of ACt between CP4-EPSPS gene and Lectin gene of the RR soybean in standard materials was generated and a linear regression equation was obtained. Quantification methods were optimized through two different real-time PCR chemistries, i.e. SYBR Green I and TaqMan, and the RR soybean contents were quantified in five standard samples and seven highly processed products by the two assays. Both methods are proved to be specific, highly sensitive and reliable for both identification and quantification of soybean DNA. The results indicate that the two optimized PCR system can be used for the practical quantitative detection of RR soybean in highly processed products.

On Enforcing Dyadic-type Homogeneous Binary Function Product Constraints in MatBase

Homogeneous binary function products are frequently encountered in the sub-universes modeled by databases,spanning from genealogical trees and sports to education and healthcare,etc.Their properties must be discovered and enforced by the software applications managing such data to guarantee plausibility.The(Elementary)Mathematical Data Model provides 17 types of dyadic-based homogeneous binary function product constraint categories.MatBase,an intelligent data and knowledge base management system prototype,allows database designers to simply declare them by only clicking corresponding checkboxes and automatically generates code for enforcing them.This paper describes the algorithms that MatBase uses for enforcing all 17 types of homogeneous binary function product constraint,which may also be employed by developers without access to MatBase.

Application of Real-time Fluorescent Quantitative PCR in Plant

Real-time fluorescent quantitative PCR （RQ-PCR） is a detection method by adding fluorescent dye or fluorescent probe into the PCR reaction system, using fluorescent signal accumulation to monitor amplification reactions of PCR reaction process, and finally the unknown template can be quantitatively analyzed through the standard curve. So the detection level of PCR has improved from the qualitative to the quantitative. In order to provide a theoretical reference for further application, the principle, classification, advantages and disadvantages of RQ-PCR were intro- duced, and its application and progress in plants in recent years were reviewed.

Nuclear decay database in fission product mass region

Accurate and reliable nuclear decay databases are essential for fundamental and applied nuclear research studies.However,decay data are not usually as accurate as expected and need improvement.Hence,a new Chinese nuclear decay database in the fission product mass region(A=66−172)based on several major national evaluated data libraries has been developed under joint efforts in the CNDC working group.A total of 2358 nuclides have been included in this decay database.Two main data formats,namely ENSDF and ENDF,have been adopted.For the total meanβandγenergies,available data from total absorption gamma ray spectroscopy measurements have been adopted.For some nuclides without experimental measurements,theoretically calculated values have been added.

A sensor transaction scheduling algorithm for maintaining real-time data temporal validity

A new scheduling algorithm called deferrable scheduling with time slice exchange (DS-EXC) was proposed to maintain the temporal validity of real-time data. In DS-EXC, the time slice exchange method was designed to further defer the release time of transaction instances derived by the deferrable scheduling algorithm (DS-FP). In this way, more CPU time would be left for lower priority transactions and other transactions. In order to minimize the scheduling overhead, an off-line scheme was designed. In particular, the schedule for a transaction set is generated off-line until a repeating pattern is found, and then the pattern is used to construct the schedule on-line. The performance of DS-EXC was evaluated by sets of experiments. The results show that DS-EXC outperforms DS-FP in terms of increasing schedulable ratio. It also provides better performance under mixed workloads.

An Efficient Secure Real-Time Concurrency Control Protocol

Secure real-time databases must simultaneously satisfy two requirements in guaranteeing data security and minimizing the missing deadlines ratio of transactions. However, these two requirements can conflict with each other and achieve one requirement is to sacrifice the other. This paper presents a secure real-time concurrency control protocol based on optimistic method. The concurrency control protocol incorporates security constraints in a real-time optimistic concurrency control protocol and makes a suitable tradeoff between security and real-time requirements by introducing secure influence factor and real-time influence factor. The experimental results show the concurrency control protocol achieves data security without degrading real-time perform ance significantly.

Research on Real-time Data Sharing in Power Integrated Automation System

The Power Integrated Automation System has a large amount of the real-time data, it needs to achieve data sharing in different modules in its own system, sometimes even needs to be shared with the other systems. The thesis discusses the characteristics and the ways of the real-time data sharing in the first place. Then, it compares the merits and drawbacks in different ways. Besides, it gives a viable resolution in different aspects, such as the design of the real-time database, the framework of the communication system and the design of the communication software, as well as the real-time data sharing in different systems.

Can environmental regulations achieve both profitability and profit quality?A natural experiment based on the China Cleaner Production Standards

Numerous studies evaluated the effects of end-of-pipe control environmental regulations(EER).However,few scholars discussed the effects of process management environmental regulations(PER),such as the China Cleaner Production Standards(CCPS)implemented by the country's Ministry of Ecology and Environment.Using data on China's manufacturing enterprises,this paper adopts the CCPS policies as quasi-natural experiments and uses differences-in-differences(DID)methods to analyze their effects on enterprise profitability and profit quality,respectively.The results show that:first,the CCPS significantly improve both profitability and profit quality;that is,the implementation of the environmental regulation policy plays a significant role in improving enterprise profit rates and cash flows.Second,for the profitability mediator effects,the short-term Porter effect of CCPS is not significant but shows the opposite during the lag period and significantly reduces the management cost and wage levels,comprehensively promoting enterprise profitability.Third,for the profit quality meditator effects,environmental regulations improve the enterprises'cash flow by reducing management costs and increasing government subsidies;however,its effect on bank credit subsidies is not significant.Fourth,for the moderator effects,the environmental regulations'effect on enterprises profitability and profit quality depends on the strategic interaction among local governments,the scale and ownership of the enterprise,and regional differences.That is,the strategic interaction weakens the effect of environmental regulations on enterprise performance.Environmental regulations have a stronger influence on profitability and profit quality for large-scale,state-owned,and coastal enterprises.