Pulsed flow chemistry. A new approach to the generation of concentration profiles in flow analysis

1998 ◽  
Vol 35 (3) ◽  
pp. 97-101 ◽  
Author(s):  
Xue D. Wang ◽  
Terence J. Cardwell ◽  
Robert W. Cattrall ◽  
Graeme E. Jenkins
Keyword(s):  
Flow Analysis ◽  
Flow Chemistry ◽  
Concentration Profiles ◽  
New Approach ◽  
Pulsed Flow

Pulsed flow chemistry: a new approach to solution handling for flow analysis coupled with chemiluminescence detection

The Analyst ◽  
2000 ◽  
Vol 125 (10) ◽  
pp. 1869-1874 ◽  
Author(s):  
Simon W. Lewis ◽  
Paul S. Francis ◽  
Kieran F. Lim ◽  
Graeme E. Jenkins ◽  
Xue D. Wang
Keyword(s):  
Flow Analysis ◽  
Flow Chemistry ◽  
Chemiluminescence Detection ◽  
New Approach ◽  
Pulsed Flow

scholarly journals Modern Flow Analysis

Molecules ◽  
2020 ◽  
Vol 25 (12) ◽  
pp. 2897
Author(s):  
Paweł Kościelniak
Keyword(s):  
Flow Analysis ◽  
Flow Chemistry ◽  
Special Issue ◽  
Good Picture ◽  
Cross Sectional ◽  
Current Trends

A brief overview of articles published in this Special Issue of Molecules titled “Modern Flow Analysis” is provided. In addition to cross-sectional and methodological works, there are some reports on new technical and instrumental achievements. It has been shown that all these papers create a good picture of contemporary flow analysis, revealing the most current trends and problems in this branch of flow chemistry.

scholarly journals Multi-Criteria Analysis and Prediction of Network Incidents Using Monitoring System

2017 ◽  
Vol 1 (1) ◽  
pp. 29 ◽  
Author(s):  
Lukas Macura ◽  
Miroslav Voznak
Keyword(s):  
Monitoring System ◽  
Network Flow ◽  
Flow Analysis ◽  
Mathematical Methods ◽  
New Approach ◽  
Creative Commons ◽  
Data Flows ◽  
Data Correlations ◽  
Computationally Intensive ◽  
Network Technologies

Today, network technologies can handle throughputs up to 100Gbps, transporting 200 million packets per second on a single link. Such high bandwidths impact network flow analysis and as a result require significantly more powerful hardware. Methods used today concentrate mainly on analyzes of data flows and patterns. It is nearly impossible to actively look for anomalies in network packets and flows for a small amount of change of monitoring patterns could result in big increases in potentially false positive incidents. This paper focuses on multi-criteria analyzes of systems generated data in order to predict incidents. We prove that systems generated monitoring data are an appropriate source to analyze and enable for much more focused and less computationally intensive monitoring operations. By using appropriate mathematical methods to analyze stored data it is possible to obtain useful information. During our work, some interesting anomalies in networks were found by utilizing simple data correlations using monitoring system Zabbix. We concluded that it is possible to declare that deeper analysis is possible due to Zabbix monitoring system and its features like Open-Source core, documented API and SQL backend for data. The result of this work is a new approach to the analysis containing algorithms which allow to identify significant items in monitoring system. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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