Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/609080
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2024-12-24T06:15:16Z | - |
dc.date.available | 2024-12-24T06:15:16Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/609080 | - |
dc.description.abstract | Abstract is available with the attachments | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Prediction of Human Performance Using Eeg Data to Improve Safety and Productivity | |
dc.title.alternative | ||
dc.creator.researcher | Raju, Gunda Yuga | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Metallurgy and Metallurgical Engineering | |
dc.description.note | ||
dc.contributor.guide | Gupta, Suprakash and Singh, Lalit Kumar | |
dc.publisher.place | Varanasi | |
dc.publisher.university | Indian Institute of Technology IIT (BHU), Varanasi | |
dc.publisher.institution | Mining Engineering | |
dc.date.registered | 2017 | |
dc.date.completed | 2023 | |
dc.date.awarded | 2023 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Mining Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 157.71 kB | Adobe PDF | View/Open |
02_prelims pages.pdf | 2.04 MB | Adobe PDF | View/Open | |
03_contents.pdf | 1.35 MB | Adobe PDF | View/Open | |
04_abstract.pdf | 626.74 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 2.75 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 5.55 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 8.96 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 4.38 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 2.3 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 8.63 MB | Adobe PDF | View/Open | |
11_chapter 6.pdf | 1.97 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 2.13 MB | Adobe PDF | View/Open |
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