Mrs Punidha A
Designation Not Listed
Organization Not Listed
Tamil Nadu
Expertise:
Computer Science Software Engineering
23
Publications
0
Projects
23
Scopus Citations
15
CrossRef
Scopus
23
Citations
2
h-index
CrossRef
15
Citations
2
h-index
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Professional Recognition
Rajayapuraskar Award
2005
Governer
Guinness World Records
2021
GUVI Geek Network Private Limited & AICTE India
Best Paper
2020
2nd International Conference on Interdisciplinary Research and Physical Sciences (ICIRPS -2020)
Innovation Ambassador
2021
MoE's Innovation Cell & AICTE
Innovation Ambassador training (Advanced Level
2021
MoE's Innovation Cell & AICTE, New Delhi
Community & Membership
Timetable Committee
In-chargeCurriculum Development Cell
InchargeGoverning Council Meet
In-chargePlanning and Evaluation
InhargeScrutiny Committee
Scrutiny MemeberInstitute Innovation Cell
MemberNIRF
NIRF Team MemberIFERP
LifetimeInstitute Innovation Council
AmbassadorInternational Association of Engineers (IAENG)
MemberPersonal Details
Master of Engineering
2015
N/A
Bachelor of Engineering
2011
N/A
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No information is available at this time.
Engineering and Technology
Scholarly Work
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Artificial Intelligence and Internet of Things based Applied Manpower Safety control for Micro,small and Medium Enterprises
Coimbatore Institute of Technology
Coimbatore-14
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Patent No. :
Filled
Filed :
05-08-2020
Published :
09-04-2020
Filed
A music playing system and device for smart sensing of mind state of the listener and playing tunes
1) PUNIDHA ANGUSAMY 2) RAJINSHA SAHAYA RAJ 3) RUDHRADHARSHINI ASOKAN 4) KEERTHANA BOOPATHI 5) VANIPRIYA MOORTHI
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Patent No. :
201941007423
Filed :
26-02-2019
Published :
08-03-2019
Published
Scholarly Publications
Ensuring testing effectiveness and accuracy through software reliability model
Malicious spam injection attack detection on social webpage posts
Open AccessMalicious attack identification using deep non linear bag-of-words (FAI-DLB)
Open AccessFirmware Injection Detection on IoT Devices Using Deep Random Forest
10.1007/978-981-15-7078-0_52
Scopus: 1
Firmware Attack Detection on Gadgets Using Ridge Regression (FAD-RR)
Firmware Attack Detection on IoT Devices Using Deep Binary Pattern Classification Mining (FA-PCM)
Karger’s Randomness of Graphs to Detect XSS Attacks on IoT Devices
Deep learning to protect cyber attack on cloud tools (Dlp-cac)
Showing 1 to 8 of 23 publications