Assessment of Water Quality Physicochemical Parameters Using Association Rule Mining for River Narmada | Chapter 2 | Science and Technology - Recent Updates and Future Prospects Vol. 7

 

Objective: The objective of this study is to analyze the various water quality parameters of the Narmada River and to find hidden relationships between them so that it can suggest some decision plans or policies to predict or classify the water quality.

 

Background: Increasing demand for surface water supplies has caused enormous pressure on freshwater ecosystems worldwide to plug the gap in demand for water, many regions of the world have relied heavily on groundwater to meet needs. There have been huge changes in river water quality during the last 10 years. This may be due to the great involvement of human activities and industrial waste.

 

Methods: In this study, we find an approach to water quality management through Association or correlation studies between various water quality parameters. The Data Mining Technique called Association Rule Mining (Apriori Algorithm) is used to find and extract some rules or relationships between various water quality parameters for the Narmada River at Harda and Hoshangabad districts of Madhya Pradesh.

 

Findings: The study explores the features of WEKA and its function by importing dataset samples and experimenting with learning datasets. The experiment is limited to a pre-given dataset, the Water Quality Data of Handia (District Harda) and Hoshangabad, M. P., from 1990 to 2010 of River Maa Narmada. Nine parameters were selected for the experiments, categorized into four classes based on pollutant index: A, B, C, and D. The results show that the WEKA Explorer runs an environment for association and parameter setting during experiments. The study found some basic interesting rules, such as the need for regular water treatment before consumption, the need for regular water treatment, and the need for regular water treatment.

 

The study analysed the relationship between water quality parameters using association rules. It was found that a decrease in NH3-N concentration leads to poor water quality at one level. For a constant pH value, BOD is strongly related to DO. The study concluded that water quality improves when BOD concentration decreases for the same pH value. The results showed that BOD concentration is higher in the Hoshangabad District than in the Harda District, resulting in poor surface water quality at one level. The study also found a relationship between NH3_N and O_PO4, with a decrease in NH3_N causing water quality to decline by one level. The study concluded that industrial centers' inclusions and DO concentrations have a reverse relation, with a decrease in DO increasing water pollution. The study recommends further research on other important water quality parameters to understand their effects on rivers.

 

Application: This research presents a model with actual data both for spatial and temporal patterns and the benefits of employing data mining techniques towards the improvement of water quality management plans. These results conclude that there is an urgent need for strict regulatory monitoring for water quality maintenance in the river system in Hoshangabad District.

 

Author(s) Details

 

Sanjeev Gour

Department of Computer Science, Medi-Caps University, Indore, M.P., India.

Mamta Gour

Department of Chemistry, Medi-Caps University, Indore, M.P., India.

Please see the link:- https://doi.org/10.9734/bpi/strufp/v7/949

Generalized Association Rules for ER Models by Using Mining Operations on Fuzzy Datasets | Chapter 9 | Recent Progress in Science and Technology Vol. 6

 Today implausible story world is functioning in an extreme-competitive atmosphere. However, the business wholes have realized that the key to endurance and sustainability of the utilization of the basic document file which is got from various trade processes. In other words, it means that the competitiveness is worked out by means of deal with the dataset and ensuring that the styles and patterns provide awareness into the decision making process. However, conclusion making is complex and complicated as various factors need expected taken into concern. These factors produce the concept of the fluffy datasets. The fuzzy datasets further decrease the scope of the currents and patterns so that familiar accurate decisions maybe obtained.The paper inquires to address the issues of the fuzzy datasets in agreements of bringing in adulthood in the decision making process by guaranteeing that the association rule excavating processes are able to pay more accuracy and accuracy in the decision making processes. Further, the paper seeks to address the issues of the individual relationship forming that exists in the table tables and the means and device deployed to overcome the issues and challenges formal by ER modelling. The projected study aims to extend the existent algorithms comprising of Extended Apriori and Apriori star to decide a new algorithm. The gift of the study results in an attempt to standardize algorithms for judgment the most appropriate come into being tables comprising of fluffy data.

Author(s) Details:

Praveen Arora,
Jagan Institute of Management Studies, New Delhi, India.

Sanjive Saxena,
Jagan Institute of Management Studies, New Delhi, India.

Deepti Chopra,
Jagan Institute of Management Studies, New Delhi, India.

Please see the link here: https://stm.bookpi.org/RPST-V6/article/view/9875

Study on Codon Modulo Cryptosystem for Privacy Preservation of Vertically Partitioned Outsourced Data | Chapter 12 | Current Approaches in Science and Technology Research Vol. 12

 Data is transferred across the cloud in a variety of ways. It is critical to protect data from unapproved users gaining access to it in any organisation. The information refuge is ensured by encoding plain text into an incomprehensible configuration using cryptographic computations, and these techniques are advocated for scrambling the text to ensure data security from aggressors. Deoxyribo Nucleic Acid (DNA) is a type of encryption used to protect data in distributed computing systems. To ensure security for transactional data, a Codon Modulo Cryptography-based Algorithm for vertically partitioned cloud data is used in this research. To aggregate the Association Rules among the Frequent Items in a scrambled exchange of vertically partitioned information base, Affiliation Rule Mining and Frequent Itemset techniques are used. The suggested Codon Modulo technique is compared to the traditional Homomorphic Encryption in the demonstration of Rule Mining computations such as Apriori, FP-Growth, and Eclat. The results show that the suggested algorithm outperforms Homomorphic Encryption in terms of performance while maintaining a good level of security.

Author (S) Details

M. Yogasini
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli-6270122, India.

Dr. B. N. Prathibha
Department of Computer Science, G. Venkataswamy Naidu College, Kovilpatti, Thoothukudi-628502, India.

View Book :- https://stm.bookpi.org/CASTR-V12/article/view/2620