Dr K.Sireesha, Associate Professor(CSE)

PUBLICATIONS

· “A Novel Approach for recognising Helmetless Motorcycle Riders with Registration number “International conference on recent innovations in engineering and technology (ICRIET-2023) march 2023

· “Phishing and Sybil Enhanced behaviour Processing and Footprint Algorithms in Vehicular Ad Hoc Network” International Journal of Safety and Security Engineering (IJSSE). Vol. 12, No. 1, February, 2022, pp. 83-96. https://doi.org/10.18280/ijsse.120111 [Scopus indexed]

· “An Implementation of Hybrid Approach for Sybil Attacks In Vehicular Ad-Hoc Networks (VANET)” International Journal of Advanced Computer Science and Applications (IJACSA). Vol. 13, No. 2, March, 2022, pp. 564-577. https://doi.org/10.21817/indjcse/2022/v13i2/221302162 [Scopus indexed]

· ” Sybil Attack Detection in VANET Using Machine Learning Approach” Ingénierie des Systèmes d’Information (ISI) .Volume 27, Number 4, August 2022 pp: 605-611 https://doi.org/10.18280/isi.270410 [Scopus indexed].

· "A Survey of VANET Security Models and its Issues on Node Level Data Transmission," 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), Feb 2022, pp. 1409-1417, DOI: 10.1109/ICAIS53314.2022.9742751.https://ieeexplore.ieee.org/document/9742751 [Scopus indexed]

· “Survey of Vanet networks “published paper in International conference on Advancing Knowledge from Multidisciplinary Perspectives in Engineering and Technology ICAKMPET-2019 organized by IFERP Institute for Engineering Research and Publication on April 5th and 6th, Visakhapatnam.

· “I Shopping: Intelligent Shopping and Predicate Analysis System Using Data Mining” National conference on Innovative Technologies and Data Communication Engineering(NCITDEC), SSRG International Journal of Computer Trends and Technology (IJCTT) Special Issue – April 2017,ISSN: 2231-2803

· “Secure and Reliable Data Sharing For Dynamic Group Members through Fine-Grained Access Control in Cloud Environment” published paper in National conference on Innovative Technologies and Data Communication Engineering(NCITDEC) in SSRG International Journal of Computer Trends and Technology (IJCTT) - Special Issue – April 2017,ISSN: 2231-2803

· “Detecting Fraud Rating For Mobile Apps” published paper in National conference on Innovative Technologies and Data Communication Engineering(NCITDEC) in SSRG International Journal of Computer Trends and Technology (IJCTT) - Special Issue – April 2017,ISSN: 2231-2803

· “Progressive Duplicate Detection “National Conference on Recent Trends in Advanced Computing, IJRCSE SPECIAL ISSUE NCRTIAC2K16, 30th APRIL 2016- ALIET.

· “Progressive And Scalable Approaches for Duplicate Detection” International Journal of Professional Engineering Studies Volume viii Issue 1 / 47-53 Dec 2016.

· “Attenuation of Co-Channel interference in femtocell networks” International Journal of Applied Engineering Research ISSN 0973-4562, Vol 10, No 3 (2015), [Scopus indexed]

· “Diminution of Co-Channel Interference in Femtocell Networks” Journal of Mobile Computing, Communications & Mobile Networks, STM Journals,Vol 1,Issue 1,March 2014

· “An Overview and Analysis of Private and Public key DNA Cryptography” International Journal Of Technological Exploration and Learning (IJTEL) ,Vol. 02, No. 6, ISSN: 2319-2135 Dec-2013

· “Voice recognition browser for reduced vision and vision loss Learners” in International Journal of Scientific & Engineering Research (IJSER), Vol. 2, Issue: 12, ISSN: 2229-5518 Dec -2011.

“PROGRESSIVE AND SCALABLE APPROACHES FOR DUPLICATE DETECTION” International journal of Professional Engineering Studies Volume viii/Issue1/Dec 2016

FDP'S ATTENDED

1. Attended online short term course on “Data visualization for Deep Learning using power BI and Tableau” conducted by NIT Warangal and VNRVJIET Hyderabad from Feb 23rd to 28th 2023.

2. Participated in one week National level FDP on cloud infrastructure(aws) in collaboration with Brain o vision solutions and AICTE from August 21^stto August 25^th2023 organized by Andhra Loyola Institute of Engineering and Technology.

3. Participated in the AICTE Recognized Faculty Development Programme on Machine Learning and Predictive Analysis using Python conducted by NITTR Chandigarh from 20/11/2023 to 24/11/2023 (One Week) at Andhra Loyola Institute of Engineering and Technology, Vijayawada, Andhra Pradesh.

4. Participated in the AICTE Recognized Faculty Development Programme on AI/ML and Data Science for Industry 4.O(Intermediate Level ) conducted by NITTR Chandigarh from 29/01/2024 to 02/02/2024 (One Week) at Andhra Loyola Institute of Engineering and Technology, Vijayawada, Andhra Pradesh

5. Participated in the AICTE Recognized Faculty Development Programme on Data Science using Python conducted by NITTR Chandigarh from 19/02/2024to 23/02/2024 (One Week) at Andhra Loyola Institute of Engineering and Technology, Vijayawada, Andhra Pradesh.

6. Participated online FDP / Course on Block Chain Technology from April 21^st to April 28^th2020 organized by Electronics and ICT Academy ,IIT Roorkee .

7. Completed an online course FDP on Digital Image Processing using Mat Lab from April 24^th 2020 to 27^th April 2020 organized by skilltohire.com

8. Participated online FDP On Internet Of Things By Sons India Software from 29^th April 2020 to 30^th April 2020

9. Participated online FDP on ML and AI organized by ALIET on 4^th May 2020 to 6^th May 2020.

10. Participated in National level FDP on “Tools for Online Class room Post Covid-19” from 18^th may 2020 to 20^th may 2020 organized by P.B.Siddartha college of Arts and Science,Computer society of India-vijayawada

11. Attended online one week workshop from 6^th July to 10^th July on Blended E-Learning organized by JNTUniversity College of Engineering,Vizianagaram in association with Computer society of India.

12. Participated in 7 day online National Workshop on “An Interactive Approach for Online Design, Develop and Delivery for higher education” from 6^th May 2020 to 12^th May 2020 organized by Panimalar Engineering College,Chennai.

13. Participated in 5 days FDP from 4^th May 2020 to 8^th May 2020 on Python 3.4.3 organized by Satyabhama institute of science and Technology Chennai, In association with IIT Bombay, Spoken Tutorial.

14. Worked as Faculty coordinator for International hands on workshop on “Angular JS” on 26^th June 2020 Organized by Brain O Vision Solutions India Pvt Limited in association with National Youth Council of India.

15. Completed Machine Learning e learning course organized by TATA steel capability development on may 17^th 2020

16. Participated in Faculty focus program on Experiential learning using virtual labs on 30th may 2020 organised by UntieUp.

Participated in the VIRTUAL SUMMIT on "COVID-19 : Impact on Education, Technology, Environment & Mankind",30th MAY,2020

DWDM

SYLLABUS:

Course Objectives:

The main objective of the course is to

• Introduce basic concepts and techniques of data warehousing and data mining

• Examine the types of the data to be mined and apply pre-processing methods on raw data

• Discover interesting patterns, analyze supervised and unsupervised models and estimate the

accuracy of the algorithms.

UNIT I:

Data Warehousing and Online Analytical Processing: Data Warehouse: Basic concepts, Data Warehouse Modelling: Data Cube and OLAP, Data Warehouse Design and Usage, Data Warehouse Implementation, Introduction: Why and What is data mining, What kinds of data need to be mined and patterns can be mined, Which technologies are used, Which kinds of applications are targeted.

UNIT II:

Data Pre-processing: An Overview, Data Cleaning, Data Integration, Data Reduction, Data Transformation and Data Discretization.

UNIT III:

Classification: Basic Concepts, General Approach to solving a classification problem, Decision Tree Induction: Attribute Selection Measures, Tree Pruning, Scalability and Decision Tree Induction, Visual Mining for Decision Tree Induction.

UNIT IV:

Association Analysis: Problem Definition, Frequent Item set Generation, Rule Generation: Confident Based Pruning, Rule Generation in Apriori Algorithm, Compact Representation of frequent item sets, FP Growth Algorithm.

UNIT V:

Cluster Analysis: Overview, Basics and Importance of Cluster Analysis, Clustering techniques, Different Types of Clusters; K-means: The Basic K-means Algorithm, K-means Additional Issues, Bi-secting K Means,

Course Outcomes:

By the end of the course student will be able to

• Illustrate the importance of Data Warehousing, Data Mining and its functionalities and Design schema for real time data warehousing applications.

• Demonstrate on various Data Preprocessing Techniques viz. data cleaning, data integration, data transformation and data reduction and Process raw data to make it suitable for various data mining algorithms.

• Choose appropriate classification technique to perform classification, model building and evaluation.

• Make use of association rule mining techniques viz. Apriori and FP Growth algorithms and analyze on frequent item sets generation.

• Identify and apply various clustering algorithm (with open source tools), interpret, evaluate and report the result.

DWDM LAB MANUAL