A research on unified storage management and access technology applied in power network dispatch and control big data

2017 ◽  
Author(s):  
Peng Liu ◽  
Xiao Han ◽  
Zhenjing Liu ◽  
Zhixiang Ji
Keyword(s):  
Big Data ◽  
Storage Management ◽  
Power Network ◽  
Access Technology ◽  
And Control

scholarly journals Tuberculosis in Epidemic Prevention and Control Based on Big Data Technology

2021 ◽  
Vol 1881 (4) ◽  
pp. 042036
Author(s):  
Jiao Tan ◽  
Yonghong Ma ◽  
Ke Men ◽  
Jing Lei ◽  
Hairui Zhang ◽  
...  
Keyword(s):  
Big Data ◽  
Prevention And Control ◽  
And Control ◽  
Big Data Technology

Off-office audit of natural resource assets and water pollution: a quasi-natural experiment in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaowei Ma ◽  
Muhammad Shahbaz ◽  
Malin Song
Keyword(s):  
Water Pollution ◽  
Big Data ◽  
Water Resources ◽  
Natural Resource ◽  
Prevention And Control ◽  
Industrial Structure ◽  
Dynamic Effect ◽  
Content Type ◽  
Audit System ◽  
And Control

PurposeThe purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.Design/methodology/approachThis study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.FindingsThe implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.Practical implicationsThese findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.Originality/valueThis study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.

scholarly journals RESEARCH ON REMOTE OPERATING SYSTEM OF PICKING ROBOT BASED ON BIG DATA AND WIFI

2021 ◽  
pp. 447-456
Author(s):  
Beibei Sun
Keyword(s):  
Operating System ◽  
Big Data ◽  
Remote Monitoring ◽  
Agricultural Production ◽  
Recognition System ◽  
Main Mode ◽  
Agricultural Robots ◽  
Remote Monitoring System ◽  
Modern Agriculture ◽  
And Control

Agricultural mechanization has become the main mode of agricultural production and represents the development direction of modern agriculture. The amount of data generated in the agricultural production process is extremely huge, so it is necessary to introduce the concept and analysis method of big data. Combining agricultural robots with big data can improve the performance and application effect of robots. This paper combines big data, WLAN technology and robot technology to realize man-machine remote cooperation platform. This gives full play to the advantages that people are good at object recognition and robots are good at execution, and improves the fruit picking efficiency. The target fruit positioning and recognition system aided by machine vision is adopted to realize the accurate positioning of the fruit to be picked. Design of LFM control signal fitting based on big data clustering. In order to verify the feasibility of the scheme, taking the tomato picking robot as an example, the communication error and control accuracy using big data and WIFI (Wireless Fidelity) technology were tested, and the positioning and navigation efficiency with and without remote monitoring system was compared. Test results show that using big data and WIFI remote monitoring technology can effectively improve the efficiency and accuracy of positioning and navigation of remote operating system, which is of great significance for the design of automatic control system of picking robot.

scholarly journals Enhancement the stability of power system using optimal location of FACTS devices

2020 ◽  
Vol 18 (2) ◽  
pp. 648
Author(s):  
Ali Najim Abdullah ◽  
Ahmed Majeed Ghadhban ◽  
Hayder Salim Hameed ◽  
Husham Idan Hussein
Keyword(s):  
Power Network ◽  
Performance Factors ◽  
Facts Devices ◽  
Clearing Time ◽  
Thyristor Controlled Series Capacitor ◽  
Overall Performance ◽  
Set Up ◽  
The Stability ◽  
And Control ◽  
Better Than

<p><span>This paper proposes a steady-state of the Static Var Compensator (SVC) &amp; Thyristor Controlled Series Capacitor (TCSC) set up for enhancing the damping overall performance and growing the integral clearing time (CCT) of a power network. The indispensable clearing time is carried out through increasing the time fault interval until the gadget loses stability. Increasing the CCT can be contribute to reliability of the safety gadget, decrease the protection machine ranking and cost. In order to attain most enhancement of machine stability via optimizing location, sizing and control modes of SVC and TCSC. Models and methodology for putting and designing shunt FACT’s units SVC (injected reactive strength Q) and series FACT’s devices TCSC (chose capacitive region) are examined in a 6-bus system. Performance factors are described to show validation of SVC and TCSC on extraordinary conditions. It is proven that the SVC is better than TCSC. </span></p>

scholarly journals Big data-driven stochastic business planning and corporate valuation

2018 ◽  
Vol 15 (3-1) ◽  
pp. 189-204 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Giuseppe Montesi ◽  
Giovanni Papiro
Keyword(s):  
Big Data ◽  
Research Question ◽  
Predictive Ability ◽  
Cash Flows ◽  
Data Driven ◽  
Business Planning ◽  
Information Asymmetries ◽  
Methodological Innovation ◽  
Set Up ◽  
And Control

The research question of this paper is concerned with the investigation of the links between Internet of Things and related big data as input parameters for stochastic estimates in business planning and corporate evaluation analytics. Financial forecasts and company appraisals represent a core corporate ownership and control issue, impacting on stakeholder remuneration, information asymmetries, and other aspects. Optimal business planning and related corporate evaluations derive from an equilibrated mix of top-down and bottom-up approaches. While the former follows a traditional dirigistic methodology where companies set up their strategic goals, the latter are grass-rooted with big data-driven timely evidence. Real options can be embedded in big data-driven forecasting to make expected cash flows more flexible and resilient, improving Value for Money of the investment and reducing its risk profile. More accurate and timely big data-driven predictions reduce uncertainties and information asymmetries, making risk management easier and decreasing the cost of capital. Whereas stochastic modeling is traditionally used for budgeting and business planning, this probabilistic process is seldom nurtured by big data that can refresh forecasts in real time, improving their predictive ability. Combination of big data and stochastic estimates for corporate appraisal and governance issues represents a methodological innovation that goes beyond the traditional literature and practice.

Book Reviews

2021 ◽  
Vol 51 (3) ◽  
pp. 242-244
Author(s):  
Wenjing Shen
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Operations Research ◽  
Management Science ◽  
Diverse Range ◽  
Optimization And Control ◽  
Areas Of Interest ◽  
And Control ◽  
To Receive

In Book Reviews, we review an extensive and diverse range of books. They cover theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems. In addition, we include books in other fields that emphasize technical applications. The editor will be pleased to receive an email from those willing to review a book, with an indication of specific areas of interest. If you are aware of a specific book that you would like to review, or that you think should be reviewed, please contact the editor. The following books are reviewed in this issue of INFORMS Journal on Applied Analytics, 51(3), May–June: Optimization and Control for Systems in the Big-Data Era: Theory and Applications, Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, Jun Wang; Pricing Lives: Guideposts for a Safer Society, W. Kip Viscusi.

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