Research on Multi-level Distributed Storage Method of Economic and Financial Management Database

2019 ◽  
Author(s):  
Xin Xiong ◽  
Ya-Hui Shen ◽  
Guo-Li Feng ◽  
Ming-Jing Guo ◽  
Bin Wang
Keyword(s):  
Financial Management ◽  
Distributed Storage ◽  
Storage Method ◽  
Multi Level ◽  
Management Database

scholarly journals OPENNESS OF LOCAL GOVERNMENT AND GOOD FINANCIAL MANAGEMENT

2018 ◽  
Vol 28 (5) ◽  
pp. 1607-1612
Author(s):  
Snežana Mitić ◽  
Dejan Andrejevic
Keyword(s):  
Internal Control ◽  
Financial Management ◽  
Central Government ◽  
Good Reason ◽  
Control Measures ◽  
Level Control ◽  
Finance Management ◽  
Building Maintenance ◽  
Multi Level ◽  
The Republic

The subject of the research is the local self-government, with a good reason, as it has much more contact with the daily life of citizens than the central government and it is mainly directly responsible for the state of healthcare, building maintenance, education, cleanliness and the environment, as well as for ensuring the functioning of basic systems, such as water and sewage. The third chapter is devoted to good public finance management. It is extremely important to recall the fact that the budget must integrate with other areas of financial operations, even if that business is carried out by a state body, regardless of the Treasury or the Ministry of Finance. The public sector debt has become a "deceptive factor" that achieves budget stability. Internal control measures should be introduced into each organization and incorporated into its procedures. The new concept of the budget system in public finances of the Republic of Serbia determines the efficiency of public expenditure management with the introduction of a multi-level control system. In addition to establishing a budget inspection and audit, one of the multi-level controls is the system of introducing internal control.

scholarly journals Big Earth Observation Data Integration in Remote Sensing Based on a Distributed Spatial Framework

2020 ◽  
Vol 12 (6) ◽  
pp. 972 ◽  
Author(s):  
Yinyi Cheng ◽  
Kefa Zhou ◽  
Jinlin Wang ◽  
Jining Yan
Keyword(s):  
Remote Sensing ◽  
Big Data ◽  
Data Integration ◽  
Distributed Storage ◽  
Remote Sensing Data ◽  
Earth Observation ◽  
Observation Data ◽  
Integration Framework ◽  
Sensing Data ◽  
Storage Method

The arrival of the era of big data for Earth observation (EO) indicates that traditional data management models have been unable to meet the needs of remote sensing data in big data environments. With the launch of the first remote sensing satellite, the volume of remote sensing data has also been increasing, and traditional data storage methods have been unable to ensure the efficient management of large amounts of remote sensing data. Therefore, a professional remote sensing big data integration method is sorely needed. In recent years, the emergence of some new technical methods has provided effective solutions for multi-source remote sensing data integration. This paper proposes a multi-source remote sensing data integration framework based on a distributed management model. In this framework, the multi-source remote sensing data are partitioned by the proposed spatial segmentation indexing (SSI) model through spatial grid segmentation. The designed complete information description system, based on International Organization for Standardization (ISO) 19115, can explain multi-source remote sensing data in detail. Then, the distributed storage method of data based on MongoDB is used to store multi-source remote sensing data. The distributed storage method is physically based on the sharding mechanism of the MongoDB database, and it can provide advantages for the security and performance of the preservation of remote sensing data. Finally, several experiments have been designed to test the performance of this framework in integrating multi-source remote sensing data. The results show that the storage and retrieval performance of the distributed remote sensing data integration framework proposed in this paper is superior. At the same time, the grid level of the SSI model proposed in this paper also has an important impact on the storage efficiency of remote sensing data. Therefore, the remote storage data integration framework, based on distributed storage, can provide new technical support and development prospects for big EO data.

scholarly journals Problems and Prospects of Accounting Management in the Digital Economy

2020 ◽  
Vol 7 (5) ◽  
pp. 6-14
Author(s):  
A. U. Panakhov
Keyword(s):  
Financial Management ◽  
Systematic Approach ◽  
Management Accounting ◽  
Process Models ◽  
Managerial Accounting ◽  
Accounting Management ◽  
Multi Level ◽  
Business Data ◽  
Modern Technologies ◽  
Selection Of

There is an active digitalization of the collecting processes, consolidating and analyzing business data in the modern economy. Against this background, many classical problems of managerial accounting still remain unresolved, among which the selection of cost objects, the search for optimal methods for calculating costs, and the integration of various types and levels of accounting among themselves. The goal of the paper is to reveal key features of management accounting development in modern enterprises. The methodological basis of the work is a systematic approach, reflected in the idea of management accounting as a multi-level system that combines methodological, organizational and infrastructural aspect. The result of the study is the disclosure of the imbalance problems associated with increased attention to higher levels of management accounting without deepening the study of lower levels of business data. There are proposed the following directions of management accounting development: further division of accounting objects; expanding the possibilities of solving the problems of calculating costs due to modern technologies; integration of cost accounting with process models, which maintained in companies today outside the framework of accounting management. The results may be of interest to researchers, practitioners in the financial management and IT fields

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