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Related Concept Videos

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
Precipitation Titration: Endpoint Detection Methods01:19

Precipitation Titration: Endpoint Detection Methods

In argentometric precipitation titrations, endpoints can be detected visually by the Mohr, Volhard, and Fajans methods. In the Mohr method, adding a soluble chromate indicator gives an initial yellow color to the analyte solution. As the titrant is added, the first excess of silver ions forms a red silver chromate precipitate, marking the endpoint. The solution pH should be maintained at about 8 by adding solid CaCO3.
In the Volhard method, a standard excess of AgNO3 is first added to the...
Precipitation Gravimetry01:03

Precipitation Gravimetry

Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...

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Related Experiment Video

Updated: May 21, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
12:50

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

A data-mining approach to predict influent quality.

Andrew Kusiak1, Anoop Verma, Xiupeng Wei

  • 1Department of Mechanical and Industrial Engineering, The University of Iowa, 3131 Seamans Center, Iowa City, IA 52242, USA. andrew-kusiak@uiowa.edu

Environmental Monitoring and Assessment
|June 12, 2012
PubMed
Summary
This summary is machine-generated.

Predicting carbonaceous biochemical oxygen demand (CBOD) in wastewater is key for energy management. This study developed data-driven models to accurately forecast CBOD levels up to five days ahead, even with missing data.

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Last Updated: May 21, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
12:50

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Area of Science:

  • Environmental Engineering
  • Data Science

Background:

  • Accurate prediction of influent water quality is crucial for efficient energy management in wastewater treatment plants.
  • Key water quality metrics include carbonaceous biochemical oxygen demand (CBOD), potential of hydrogen (pH), and total suspended solids (TSS).
  • Gaps in time-series data due to industrial data acquisition limitations hinder accurate CBOD monitoring.

Purpose of the Study:

  • To develop a data-driven approach for time-ahead prediction of CBOD in wastewater treatment.
  • To address challenges posed by missing CBOD data in industrial time-series datasets.
  • To investigate the impact of seasonality on CBOD prediction models.

Main Methods:

  • Utilized four data-mining algorithms: multilayered perceptron (MLP), classification and regression tree (CART), multivariate adaptive regression spline (MARS), and random forest (RF).
  • Employed experimental approaches to approximate functional relationships and fill missing CBOD data points.
  • Developed prediction models with a maximum prediction horizon of 5 days, incorporating seasonality effects.

Main Results:

  • Successfully constructed data-driven models for time-ahead CBOD prediction.
  • Demonstrated the feasibility of filling data gaps in CBOD time-series data.
  • Evaluated the performance of MLP, CART, MARS, and RF algorithms for this prediction task.

Conclusions:

  • The proposed data-driven approach effectively predicts CBOD levels in wastewater influent.
  • The methods developed can overcome limitations of industrial data acquisition systems for water quality monitoring.
  • Accurate CBOD forecasting up to 5 days ahead supports optimized energy management in wastewater treatment plants.