An Improved Intrusion Detection System Utilizing Generative Adversarial Networks.
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| Title: | An Improved Intrusion Detection System Utilizing Generative Adversarial Networks. |
|---|---|
| Authors: | Raju, B. Pandu Ranga1 balaraju.pandu@gmail.com, Rohitha, K.1 rohitha1603@gmail.com, Bhavana, K. V.1 kbhavana765@gmail.com, Mahitha, M.1 mahithareddy174@gmail.com, Sweety, M.1 sweetymangala123@gmail.com |
| Source: | Educational Administration: Theory & Practice. 2023, Vol. 29 Issue 4, p1408-1414. 7p. |
| Abstract: | In the present study an attempt has been made to investigate whether awareness towards Information and Communication Technology (ICT) is imparted among Higher Secondary School teachers by conducting research on data collected from different higher secondary schools in Tamil Nadu. During Covid pandemic, every school teachers working in Private, Government, management schools in one way or other way are forced to use the ICTs and practice online mode of delivery for teaching learning process in spite of their locality, availability of interrupted Net facilities etc. That is the motivational factor for conducting this investigation. The sample included 300 teachers (inclusive of 181 male and 119 female) randomly selected from different higher secondary schools in Tamil Nadu. The investigator himself developed a customized scale to measure the awareness on ICTs such as ETV, CD-ROM, Multimedia, Interne, EDUSAT in Arts and Science Education. The results of the presents study cleared indicate that both male and female teachers in higher secondary schools have the same level of awareness in ICTs. This study, aims to provide various possibilities to know the extent of the ICT facilities available in various educational institutions and to what extent they permit faculty members to utilize ICT for classroom Learning. [ABSTRACT FROM AUTHOR] |
| Copyright of Educational Administration: Theory & Practice is the property of Educational Administration: Theory & Practice and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 183872418 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.53555/kuey.v29i4.6399 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 7 StartPage: 1408 Titles: – TitleFull: An Improved Intrusion Detection System Utilizing Generative Adversarial Networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Raju, B. Pandu Ranga – PersonEntity: Name: NameFull: Rohitha, K. – PersonEntity: Name: NameFull: Bhavana, K. V. – PersonEntity: Name: NameFull: Mahitha, M. – PersonEntity: Name: NameFull: Sweety, M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: 2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 13004832 Numbering: – Type: volume Value: 29 – Type: issue Value: 4 Titles: – TitleFull: Educational Administration: Theory & Practice Type: main |
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