Pragmatic analysis of wastewater treatment methods from a statistical perspective

Pande, Pournima; Bhagat, Ashish

doi:10.2166/wpt.2022.153

Cited by 3 publications

(3 citation statements)

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“…In [11], a review of neural networks used for controlling activated sludge plants was carried out. Networks based on deep learning models such as «reinforcement learning» or «long short-term memory» have been shown to be effectively used to predict and plan cleaning processes.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the activated sludge composition using artificial neural networks

Sanginova

2023

TAPR

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The object of research is electron microscopic images of activated sludge, which were used to train a convolutional neural network. An important task of the process of biological wastewater treatment is the prompt determination of quantitative and qualitative changes in activated sludge, as well as the assessment of the impact of the identified changes on the efficiency of the treatment. Microscopic examination, which is a traditional tool for controlling the quality of the water-sludge mixture, does not allow to quickly detect the deterioration of the activated sludge, which can lead to its degradation, and in difficult cases – to the death of the sludge. Violation of the microbiological composition of sludge leads to improper formation of flocs, violation of the process of formation of flakes, filamentous or sludge swelling, toxicity, etc. The combination of artificial intelligence methods with existing methods of quality control of activated sludge will increase the reliability and validity of the assessment of the quality of biological treatment. A proposed methodology for analyzing the state of activated sludge using convolutional neural networks. For the purpose of training the network, images of activated sludge were prepared, which were classified into two categories – «flocs» and «bacteria with microorganisms». There are 4 subcategories in the «flocks» category: size, shape, structure, edge of the floc; in the category «bacteria with microorganisms» there are 2 subcategories: «individual bacteria and microorganisms» and «colonies». Data sets of 250, 500 and 1000 images were created for each category. The task of learning the image processing model and the criteria for evaluating the success of learning are formulated. The task of training the network was to find such a recognition function that, with a given degree of accuracy, approximates the unknown recognition function over the entire domain of its definition. The accuracy of image recognition is chosen as a learning success criterion. The model training results show that the image recognition accuracy reaches 99.98 %, and the training quality is affected by the sample size and training duration. The trained model can be used as a fast and efficient tool to detect problems with activated sludge.

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Section: Introductionmentioning

confidence: 99%

Analysis of the activated sludge composition using artificial neural networks

Sanginova

2023

TAPR

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“…Pragmatic analysis, on the other hand, goes beyond the literal meanings and unearths into the implicit meaning, context and purposive effects of the lyrics (Pande and Bhagat, 2023). This signifies that it considers how the language is used to achieve specific communicative goals (Ward et al, 1991).…”

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confidence: 99%

“…It critiques the fundamental messages that may not be explicitly stated but can be inferred based on context, cultural references and figurative language. Bearing this in mind, pragmatic analysis takes into account the broader context in which the song was written and performed (Pande and Bhagat, 2023). In other words, it considers the cultural, social and historical context, as well as the artist's justifications for creating the song.…”

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confidence: 99%

Advancing semantic and pragmatic theoretical frameworks through an analysis of Taylor Swift's "Look What You Made Me Do"

Diko

2024

Forum Linguist. Stud.

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Semantics and pragmatics, as theoretical frameworks, continue to prove their appropriateness in the examination of literary texts and conversations, as well as in songs and music. This denotes that the two theoretical frameworks cannot solely be constricted within the parameters of general linguistics; instead, they are applicable to other disciplines or subject areas. In view of this fact, this article aims to uncover the covert meanings in Taylor Swift’s “Look What You Made Me Do” lyrical song. To do this, semantic and pragmatic theoretical frameworks are applied, while the song itself is acknowledged as a primary source of data. The objective of this article is to demonstrate the development of semantics and pragmatics, as theoretical perspectives, and the ways in which meaning can be explicated using these theoretical perspectives in the chosen song and other areas of interest. Ultimately, the overall objective is to demonstrate how words, phrases and sentences may be understood differently by language users. The results and discussions validate that Taylor Swift uses different linguistic techniques, as well as metaphorical expressions to communicate her message to her audience. Nevertheless, such abilities of this singer and songwriter may not always be clear to everyone, hence the necessity to apply semantic and pragmatic theoretical lenses. The closing remarks underline the importance of continuing to develop the two theoretical perspectives beyond the limitations of general linguistics. In addition to this, the closing remarks underscore the synergetic relationship that exists between language and music.

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Long-Term Time Series Trend Analysis of Climatic Variable for Jaisalmer District in Thar Desert, Western Rajasthan, India, Using Statistical Approaches

Singh,

Choudhary

2024

J. Inst. Eng. India Ser. A

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Pragmatic analysis of wastewater treatment methods from a statistical perspective

Cited by 3 publications

References 44 publications

Analysis of the activated sludge composition using artificial neural networks

Analysis of the activated sludge composition using artificial neural networks

Advancing semantic and pragmatic theoretical frameworks through an analysis of Taylor Swift's "Look What You Made Me Do"

Long-Term Time Series Trend Analysis of Climatic Variable for Jaisalmer District in Thar Desert, Western Rajasthan, India, Using Statistical Approaches

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