Quality control of marine big data——a case study of real-time observation station data in Qingdao

Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great significance for exploiting and protecting the ocean.We used hourly mean wave height,temperature,and pressure real-time observation data taken in the Xiaomaidao station(in Qingdao,China)from June 1,2017,to May 31,2018,to explore the data quality using eight quality control methods,and to discriminate the most effective method for Xiaomaidao station.After using the eight quality control methods,the percentages of the mean wave height,temperature,and pressure data that passed the tests were 89.6%,88.3%,and 98.6%,respectively.With the marine disaster(wave alarm report)data,the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions.The mean wave height is often affected by dynamic marine disasters,so the continuity test method is not effective.The correlation test with other related parameters would be more useful for the mean wave height.

Study on Rear-end Real-time Data Quality Control Method of Regional Automatic Weather Station

[Objective] The aim was to study the rear-end real-time data quality control method of regional automatic weather station. [Method] The basic content and steps of rear-end real-time data quality control of regional automatic weather station were introduced. Each element was treated with systematic quality control procedure. The existence of rear-end real time data of regional meteorological station in Guangxi was expounded. Combining with relevant elements and linear changes, improvement based on traditional quality control method was made. By dint of evaluation and relevant check of element, the quality of temperature and pressure was controlled. [Result] The method was optimized based on traditional quality control method, and it narrowed the effectiveness of real-time data quality control. The quality check of hourly precipitation applied relevant check of hourly minimum temperature, vertical consistency check of radar data, which can effectively improve the accuracy and credibility of hourly precipitation quality control. [Conclusion] The method was on trial for one year in the quality control of real-time data in the regional automatic meteorological station in Guangxi and had gained good outcome.

Theory on real-time control of construction quality and progress and its application to high arc dam

A complete scheme for solving the key scientific problems associated with high-standard,high-intensity continuous construction of high arch dams was presented. First,based on a coupling analysis of construction system decomposition and coordination for a high arc dam,a mathematical model for real-time control of construction quality and progress that considers complex constraints was developed. Second,a method of progress control was proposed based on a dynamic simulation. Third,a dynamic quality control mechanism was established based on construction information collected using a PDA. Fourth,a system for integrating collected information,progress simulation and quality control analyses under a network environment was developed. Finally,these methods were applied to a practical project to show that each aspect of a construction process can be managed effectively and that real-time monitoring and feedback control can be realized. Our methods provide new theoretical principles and technical measures for quality and progress control in the high arc dam construction process.

Operational guidance for aeration and flow augmentation for the Chicago Area Waterway System—A case study

The Chicago Area Waterway System(CAWS)is a 133.9 km branching network of navigable waterways controlled by hydraulic structures,in which the majority of the flow is treated wastewater effluent and there are periods of substantial combined sewer overflows.The CAWS comprises a network of effluent dominated streams.More stringent dissolved oxygen(DO)standards and a reduced flow augmentation allowance have been recently applied to the CAWS.Therefore,a carefully calibrated and verified one-dimensional flow and water quality model was applied to the CAWS to determine emission-based real-time control guidelines for the operation of flow augmentation and aeration stations.The goal of these guidelines was to attain DO standards at least 95%of the time.The“optimal”guidelines were tested for representative normal,dry,and wet years.The finally proposed guidelines were found in the simulations to attain the 95%target for nearly all locations in the CAWS for the three test years.The developed operational guidelines have been applied since 2018 and have shown improved attainment of the DO standards throughout the CAWS while at the same time achieving similar energy use at the aeration stations on the Calumet River system,greatly lowered energy use on the Chicago River system,and greatly lowered discretionary diversion from Lake Michigan,meeting the recently enacted lower amount of allowed annual discretionary diversion.This case study indicates that emission-based real-time control developed from a well calibrated model holds potential to help many receiving water bodies achieve high attainment of water quality standards.

A square root information filter for multi-GNSS real-time precise clock estimation

Real-time satellite orbit and clock estimations are the prerequisite for Global Navigation Satellite System(GNSS)real-time precise positioning services.To meet the high-rate update requirement of satellite clock corrections,the computational efficiency is a key factor and a challenge due to the rapid development of multi-GNSS constellations.The Square Root Information Filter(SRIF)is widely used in real-time GNSS data processing thanks to its high numerical stability and computational efficiency.In real-time clock estimation,the outlier detection and elimination are critical to guarantee the precision and stability of the product but could be time-consuming.In this study,we developed a new quality control procedure including the three standard steps:i.e.,detection,identification,and adaption,for real-time data processing of huge GNSS networks.Effort is made to improve the computational efficiency by optimizing the algorithm to provide only the essential information required in the processing,so that it can be applied in real-time and high-rate estimation of satellite clocks.The processing procedure is implemented in the PANDA(Positioning and Navigation Data Analyst)software package and evaluated in the operational generation of real-time GNSS orbit and clock products.We demonstrated that the new algorithm can efficiently eliminate outliers,and a clock precision of 0.06 ns,0.24 ns,0.06 ns,and 0.11 ns can be achieved for the GPS,GLONASS,Galileo,and BDS-2 IGSO/MEO satellites,respectively.The computation time per epoch is about 2 to 3 s depending on the number of existing outliers.Overall,the algorithm can satisfy the IGS real-time clock estimation in terms of both the computational efficiency and product quality.

Detection and quantification of Bacillus cereus and its spores in raw milk by qPCR,and distinguish Bacillus cereus from other bacteria of the genussBacillus

Introduction:Raw milk is the basic raw material of dairy products.Bacillus cereus(B.cereus)is a typical conditional pathogenic bacteria and cold-phagocytic spoilage bacteria in raw milk.Materials and Methods:In this study,a quantitative polymerase chain reaction(qPCR)method for detecting B.cereus in raw milk was established.The specificity of the method was verified by using other Bacillus bacteria and pathogenic bacteria;the sensitivity of the method was evaluated by preparing recombinant plasmids and simulated contaminated samples;and the applicability of the method was verified using pure spore DNA.The actual sample detection was completed by using the established qPCR method.Results:The qPCR established in this study can specifically detect B.cereus in raw milk.The limit of detection of the method was as low as 200 CFU/mL,the limit of quantification ranged from 2×10^(2)to 2×10^(8)CFU/mL,and the amplification efficiency of qPCR was 96.6%.Conclusions:The method established in this study can distinguish B.cereus from other Bacillus bacteria,and spore DNA can be used as the detection object.This method has the advantages of strong specificity,high sensitivity,wide application range,and short detection time,which isexpectedtobeapplied in thedairy industry.