Experimental investigation of turning process parameter under several cutting conditions for duplex steels for minimization of cutting temperature

Arun, K.K.; Navaneeth, V.R.; Prabhu, S.; Kumar, Muralidharan; Giriraj, M.

doi:10.1016/j.matpr.2022.01.447

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…The second research direction is to use social network data to detect and identify depression. For example, the authors in [ 9 , 10 ] obtained a large amount of Twitter data, used the CES-D scale to get the user's depression state label, and analyzed the user's social network behavior data for feature extraction to construct a depression detection model, proving that Twitter data can be used to detect whether a user has depression. The authors in [ 11 ] used data from multiple blog platforms such as Yahoo Japan and Livedoor, combined with Japanese-specific language features for feature extraction.…”

Section: Related Workmentioning

confidence: 99%

Identification and Classification of Depressed Mental State for End-User over Social Media

Kumar

Thakare²,

Bhende³

et al. 2022

Computational Intelligence and Neuroscience

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In researching social network data and depression, it is often necessary to manually label depressed and non-depressed users, which is time-consuming and labor-intensive. The aim of this study is that it explores the relationship between social network data and depression. It can also contribute to detecting and identifying depression. Through collecting and analyzing college students’ microblog social data, a preliminary screening algorithm for college students’ suspected depression microblogs based on depression keywords, and semantic expansion is researched; a comprehensive lexical grammar was proposed. This research provided has a preliminary screening method based on depression keywords and semantic expansion for college students’ suspected depression microblogs, with a screening accuracy. This method forms a depression keyword table by constructing the basic keyword table and the semantic expansion based on the word embedding learning model Word2Vec. Finally, the word table is used to calculate the semantic similarity of the tested microblogs and then identify whether it is a suspected depression microblog. The experimental results on the microblog dataset of college students show that the comprehensive lexical method is better than the SDS questionnaire segmentation method and the expert lexical method in terms of screening accuracy; the comprehensive lexical approach can quickly and automatically screen out a tiny proportion of suspected doubts from a large number of college students’ microblogs. Depression Weibo can reduce the workload of experts’ annotation, improve annotation efficiency, and provide a suitable data processing basis for the subsequent accurate identification (classification problem) of patients with depression.

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Section: Related Workmentioning

confidence: 99%

Identification and Classification of Depressed Mental State for End-User over Social Media

Kumar

Thakare²,

Bhende³

et al. 2022

Computational Intelligence and Neuroscience

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show abstract

“…By considering the problems associated with high cutting temperature and high bonding at the tool working interface for titanium alloy machining, the optimal parameters for the best cutting conditions were obtained [24]. The cutting temperatures of turning super duplex stainless steel (SDSS) under dry cutting, wet cutting and air-cooled cutting conditions were investigated, and it was concluded that air-cooled machining has better cutting performance [25]. The characteristics of cutting zone temperature when turning aluminum alloy with carbide inserts was studied and the results show that the feed and the nose radius are the main factors affecting the cutting zone temperature [26].…”

Section: Introductionmentioning

confidence: 99%

Cutting mechanics and efficiency of forward and reverse multidirectional turning

Cai

Zhang

et al. 2023

International Journal of Mechanical Sciences

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Influence of machining parameters on tool wear, residual stresses, and corrosion resistance after milling super duplex stainless steel UNS S32750

Marques,

Suyama,

Antunes

et al. 2023

Int J Adv Manuf Technol

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Experimental investigation of turning process parameter under several cutting conditions for duplex steels for minimization of cutting temperature

Cited by 4 publications

References 8 publications

Identification and Classification of Depressed Mental State for End-User over Social Media

Identification and Classification of Depressed Mental State for End-User over Social Media

Cutting mechanics and efficiency of forward and reverse multidirectional turning

Influence of machining parameters on tool wear, residual stresses, and corrosion resistance after milling super duplex stainless steel UNS S32750

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