Equipments List:
| S.No. | Equipment List | Type | Quantity |
|---|---|---|---|
| 32GB RAM Rack Servers | |||
| Hewlett-Packard (HP) ProLiant DL385 G2, 4xDual-Core AMD Opteron 2218 @ 2.6GHz,8 core, 32GB RAM, 6*146GB HDD, 4NIC port, iLO 2, VT, x64 | Server | 1 | |
| Hewlett-Packard (HP) ProLiant DL385 G2, 4xDual-Core AMD Opteron 2218 @ 2.6GHz,8 core, 32GB RAM,6*146GB HDD, 4NIC port, iLO 2, VT, x64 | Server | 1 | |
| Hewlett-Packard (HP) DL165G5 Quad core CPU AMD Opteron 2354 2.20Ghz, 4 port NICs,32GB RAM, 2*500GB HDD, VT, X64 | Server | 1 | |
| Hewlett-Packard (HP) Proliant DL585 G2, 4 Dual Core AMD Opteron 8214 @ 2.2GHz Processor, 32GB RAM, 2*300GB HDD, 4 NIC Port, x64, VT | Server | 1 | |
| 16GB RAM Rack Servers | |||
| Hewlett-Packard (HP) HP DL140 G3 Intel Xeon CPU E5345 @ 2.33 GHz - 16GB RAM, 500GB HDD, 2 NIC Port, VT, x64 | Server | 1 | |
| Hewlett-Packard (HP) HP DL140 G3 Intel Xeon CPU E5345 @ 2.33 GHz - 16GB RAM, 500GB HDD, 2 NIC Port, VT, x64 | Server | 1 | |
| Hewlett-Packard (HP) ProLiant DL360 G5, 2 Quad Core intel Xeon E5430 @ 2.66GHz Processors, 16GB RAM, 120GB (3*120) HDD, 4 NIC Port, VT, X64 | Server | 1 | |
| Hewlett-Packard (HP) ProLiant DL360 G5, 2 Quad Core intel Xeon E5430 @ 2.66GHz Processors, 16GB RAM, 120GB (3*120) HDD, 4 NIC Port, VT, X64 | Server | 1 | |
| Dell PowerEdge SC1435, 2 Dual Core AMD Opteron 2212 @ 2.00GHz Processor, 16GB RAM, 500GB HDD, 2-NIC Port, VT , X64 | Server | 1 | |
| Dell PowerEdge SC1435, 2 Dual Quad-Core AMD Opteron™ 2354 @ 2.20GHz Processor, 16GB RAM, 250GB (2*250) HDD, 4-Port NIC, VT , X64 | Server | 1 | |
| Dell PowerEdge SC1435, 2 Dual Quad-Core AMD Opteron™ 2354 @ 2.20GHz Processor, 16GB RAM, 250GB (2*250) HDD, 4-Port NIC, VT , X64 | Server | 1 | |
| Dell PowerEdge(TM) 2950,2x Intel(R) Xeon(R) E5430 @ 2.66GHz 2x6MB Cache, 16GB RAM, 2*300 GB HDD,4 NIC Port, VT, X64 | Server | 1 | |
| Dell Computers(TM) Dell optiplex, E6550, Intel(R) Core(TM)2 Duo CPU 2.33GHZ,cache 4MB, RAM 4GB, HDD 160GB, DVD ROM, | Personal Computers | 40 | |
| HP 280 Microtower G8, Intel® Core™ i5-11500 @ 2.7GHz, 11 th Gen, RAM 16GB, HDD 1TB | Personal Computers | ||
Microsoft Volume License Center:
| Sl. No | Part No | Item Description | Qty |
|---|---|---|---|
| S3Y- 00001 | O365ProPlusOpenFaculty ShrdSvr ALNG SubsVL OLV E 1Mth Acdmc AP (1 Y) | 100 | |
| KW5- 00359 | WINEDU ALNG UpgrdSAPk OLV E 1Y Acdmc Ent | 100 | |
| FYS- 00001 | IntuneOpenFclty ShrdSvr ALNG SubsVL OLV E 1Y Acdmc AP | 100 | |
| 9EM- 00294 | WinSvrSTDCore ALNG LicSAPk OLV 2Lic E 1Y Acdmc AP CoreLic | 8 | |
| R18- 03497 | WinSvrCAL ALNG LicSAPk OLV E 1Y Acdmc Ent DvcCAL | 100 | |
| 228- 09538 | SQLSvrStd ALNG LicSAPk OLV E 1Y Acdmc AP | 1 | |
| 359- 05414 | SQLCAL ALNG LicSAPk OLV E 1Y Acdmc Ent DvcCAL | 20 | |
| 77D- 00161 | VSProwMSDN ALNG LicSAPk OLV E 1Y Acdmc AP | 43 |
Target users:
- UG and PG students
- Research scholars
- Faculty and Staff
Capabilities:
- Design of databases applications
- Data warehouse design and Data Mining
- Data analytics in various domains like Healthcare, Retail, Finance
- Data Preprocessing and Analytics using open source data mining tools
- Recommendation System
- Image Processing
- Deep Learning algorithms for computer vision
Work done:
Incremental Learning:
- Frequent Pattern Mining over Data Streams
- Incremental Mining of Class-Association Rules, Weighted Class Association Rules and Constraint Class-Association Rules
Predictive Analysis:
- Performance Enhancement of Data Mining Algorithms for Chronic Diseases and Medline Documents
- Prediction of Chronic Diseases using(i) Amalgam kNN,(ii) Modified Logistic Regression Model and (iii) Boosted Bayes Approach
- MEDLINE Document Classification of Diabetes Related Journals using (i) Semi- Supervised model,(ii) Optimal Rule Learning for Associative Classification (ORLAC) Approach and (iii) Expectation Maximization-Fuzzy Rule-based Classification (EM-FRBC) Approach
Computer Vision
- Waste segregation using CNN
Blockchain
- Security in Supply Chain Management
UG Projects:
- Machine Learning approach for Personalized Job Recommendation System
- Hand Gestures Recognition
- Online Exam Proctoring System
- Early Forest Fire Detection using machine learning algorithms
- Sketch Based Image Recognition to find the Person
- Virtual Lab Assistant to conduct lab sessions during Lockdown
- Human Protein Atlas – Image Classification
- Multivariate student knowledge Tracing using Convnets
- Virtual Reality for handling Glossophobia
- Customer Segmentation using machine learning In R
- Design and Development of Stylometric based Fake News Detection on Social Media using Natural Language Processing and Machine Learning
- Identification of Cardiovascular disease with minimum features using machine learning
- Plant Recognition using CNN
PG Projects:
- Employee Turnover Prediction
- Sentiment Analysis of Review (movies and products) and Twitter Data
- Prediction of Diabetes Mellitus using Logistic Regression
- Driver Drowsiness Detection using Machine Learning
- Machine Learning Approach for Organic Manure Recommendation System
- Waste segregation using IOT and CNN
No. of Journals: 15
No. of Conferences:30
Industry Interface:
- Microsoft
- IBM
- Oracle
- Honeywell
- Wipro
- CTS
- Covance/LabCorp
People:
Dr. B. Subbulakshmi
Dr. N. Anitha
Mrs. D. Priyadharshini