Dr. AMITKUMAR SUBHASHRAO MANEKAR

@ssgmce.ac.in

ASSOCIATE PROFSSOR
SHRI SANT GAJANAN MAHARAJ COLLEGE OF ENGINEERING SHEGAON



              

https://researchid.co/asmanekar24

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Computer Networks and Communications, Information Systems, Computer Engineering

19

Scopus Publications

169

Scholar Citations

6

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Deep Residual Network and Water Cloud Model-Based Soil Moisture Retrieval Using Satellite Images
    Sanjay B. Waykar, Rajesh Kadu, and Amitkumar Manekar
    Seventh Sense Research Group Journals
    - Soil moisture is a critical part of the link between land carbon cycle and surface-ground water motion. It also is vital in energy exchange between land/atmosphere; furthermore, soil moisture is an important determinant process for plant growth and productivity. By making the technique use satellite imagery, it is able to predict soil moisture content more accurately rather than using vegetation indices like the “Wide Dynamic Range Vegetation Index (WDRVI), Simple Ratio (SR), or Green Leaf Area Index (GLAI)”. A Deep Residual Network (DRN)-based “water cloud model “for soil moisture” forecasting is generated according to the vegetation indices. Additionally, soil moisture is derived using vegetation indices such as the “Wide Dynamic Range Vegetation Index (WDRVI), Simple Ratio (SR), and Green Leaf Area Index (GLAI)”. Performance of the developed DRN-based “water cloud model “was also evaluated in terms of RMSE and estimation error. The objective of this research work is to come up with a new modeling approach of soil moisture retrieval by improving “water cloud model “with satellite images and vegetation indices in one hand, and consequently to verify its performance through the application of Deep Residual Network (DRN)-based “water cloud model “on another hand. According to the experimental results, the suggested DRN-based “water cloud model “performed better than the others, with the smallest estimate error and Root Mean Square Error (RMSE) values of 0.523 and 0.69, respectively. The developed method’s estimation error is lower than that of the Semi-Empirical Water Cloud Model, Deep Multi Model Fusion Network, Genetic Algorithm (GA), Convolution Neural Network and Regression (CNNR), and Particle Swarm Optimization (PSO), respectively, at 94.14%, 65.32%, 91.63%, 63.12%, and 91.10%. The developed scheme’s RMSE is lower than that of the CNNR, PSO, Genetic Algorithm GA, Deep Multi Model Fusion Network, Semi Empirical Water Cloud Model, and 93.52%, 90.33%, 93.11%, and 89.72%, respectively.


  • Optimize Task Scheduling and Resource Allocation Using Nature Inspired Algorithms in Cloud based BDA
    A.S. Manekar and Dr. Pradeepini Gera
    NeuroQuantology Journal
    Task Scheduling and Resource allocation is a prominent research topic in cloud computing. There are several objectives associated with Optimize Task Scheduling and Resource allocation as cloud computing systems are more complex than the traditional distributed system. There are several challenges like resolving the task mapped to the node on which task to be executed. A simplified but near optimal proposed nature inspired algorithms are focus in this paper. In this paper basic idea about optimization, reliability and complexity is considered while design a solution for modern BDA (Big Data Application). Detailed analysis of experimental results, it is shown that the proposed algorithm has better optimization effect on the fair share policies which are presently available in most of the BDA. In this paper we focused on Dragonfly algorithm and Sea lion algorithms which are nature inspired algorithms. These algorithms are efficient for optimization purpose for solving task scheduling and resource allocation problem. Finally performance of the hybrid DA algorithm and Sea lion is compared with traditional techniques used for modern BDA using Hadoop MapReduce. Simulation results prove the efficacy of the suggested algorithms.


  • Deadline aware optimization in resource allocation for reducing migration cost
    Amitkumar S. Manekar and P. Gera
    Union of Researchers of Macedonia
    ,

  • Optimize Neutral Framework with Fair Share Resource Allocator for Big Data Processing on Cloud Infrastructure
    Amitkumar Manekar and Pradeepini Gera
    IEEE
    Data is precious! Data generated from myriad resources are store and treated, extracted for getting knowledge through classical machine learning techniques. The MapReduce is a programming framework that proved its efficiency and reliability for big data processing in a distributed environment. When data are generated in a cloud platform the speed and volume of data are high. MapReduce has its own limitation over processing big data. Spark has also eliminated many boundaries especially dealing with online streaming and cloud generated data. Big Data cluster management is a tedious work that needs specialized algorithms for a fair share approach. Many time resource contention problems have to address with fair-share but the performance was not satisfactory. MESOS and YARN have an implementation of the same. The proposed framework use historical job execution logs for admission control and deadline information is an additional and important part which supplied at the time of submission of the job. The work anticipates different deadline formulation explained in the result section. Finally, a comparison of justice with existing fair share allocation policies is discussed.

  • Mahaganana: An Approach to a Smart Census in India
    Jigar Wakhariya, Prakhar Gangrade, and Amitkumar Manekar
    IEEE
    In a large country like India where the population of states is equal to the population of other countries, it is very difficult to obtain the count of the population in a given minimum time and cost. Although the year 2021 is going to be the Census year for India, the 2021 Census is 8th Census (since independence) of country. In India, Census is conducted in every ten years by the government. This census is going to be very important due to many reasons. The previous censuses took place by the manual procedure that is very typical and is used since it has been introduced by the British in 1872. This procedure is very time consuming and requires large effort by mankind. So the need of the time is to simplify it. This could be simplified using technology. So we are using a Cross-Platform portal to conduct the entire process in a digital manner and introducing several changes in procedure of conduction of Census. This portal will serve to all. (i.e. Citizen, Census Officer, Ministers, etc.) and the entire procedure will be described as Mahaganana.

  • Splay: A Lightweight Video Streaming Application
    Nilesh S Inkane, Siddhi A Kotak, and Amitkumar S. Manekar
    IEEE
    Splay is a video streaming progressive web application which uses YouTube as a server and storage for videos and the app itself resides on our own desired server. Splay achieves this by using embed feature provided by YouTube and hence can even be hosted on a smaller server without carrying the load of videos. It is developed to work on any given device and any given platform provided, the given device has a browser. An app shell architecture is implemented in splay with the use of service workers and JavaScript for the technology stack. It uses React.js for developing user interfaces and achieving a single page application model for the more native-like experience. Node.js and Mongo DB are the ones powering the back end of the application. This paper basically focuses on the architecture and working of the application and our main focus is to collect all important educational videos of college including lectures, tutorials on one platform with proper content management as desired by the institute or organization using it.

  • Experimenting cloud infrastructure for tomorrows big data analytics


  • Studying cloud as IaaS for big data analytics: Opportunity, challenges


  • Cloud Based Big Data Analytics a Review
    Amit Kumar Manekar and G. Pradeepini
    IEEE

  • Big data analytics: Hadoop and tools
    Mrunal Sogodekar, Shikha Pandey, Isha Tupkari, and Amit Manekar
    IEEE
    Information technology gives utmost importance to processing of data. Some petabytes of data is not sufficient for storing large amount of data. Large volume of unstructured and structured data that gets created from various sources such as Emails, web logs, social media like Twitter, Facebook etc. The major obstacles with processing Big Data include capturing, storing, searching, sharing and analysis. Hadoop enables to explore complex data. It is an open source framework written in Java which supports parallel and distributed data processing and is used for reliable storage of data. With the help of big data analytics, many enterprises are able to improve customer retention, help with product development and gain competitive advantage, speed and reduce complexity. E-commerce companies study traffic on web sites or navigation patterns to determine probable views, interests and dislikes of a person or a group as a whole depending on the previous purchases. In this paper, we compare some typically used data analytic tools.

  • Finding outlier from large dataset using online OSPCA
    Priyanka R. Patil and Amitkumar S. Manekar
    IEEE
    Anomaly Detection is the term which is widely used in Data Mining. Anomaly Detection means Fraud Detection. Anomalous Intrusion became a key issue in security because of the heavy data in network. So it becomes hard to prevent such attacks. Previous techniques works only on batch mode means those techniques are not applied for large dataset. For this purpose it is important to find technique which provides support for large dataset. The HMM and OSPCA are the techniques which are applied for large dataset by using online updating technique. These Techniques are used in the applications such as Fraud Detections Systems like Intrusion Detection Technique.

  • A novel approach to prevent personal data on a social network using graph theory
    Neha A. Patil and Amitkumar S. Manekar
    IEEE
    Online social network such as Twitter, LinkedIn are widely used now a days. In these people lists their personal information and favorite activities which meant to be secure. Private information leakage becomes key issues with social network users. Apart from this user are hampered with various types of malicious data attacks which feel users very embarrassing in a real life. Also manual filtering for such a large data is not feasible at all. So various users stay away from social network sites to avoid such activities the social network architecture should be improved so that normal user can take a relief. Proposed work is an automatic prevention mechanism for such a heavy data using NLP and data mining approach. Objective of work is creation of real time rule sets to filter data using graph theory.

  • Radio frequency based navigation and management system for KUMBH
    Ajay Sharma, Amit Raut, Pankaj Donde, and Amit Kumar Manekar
    IEEE
    In country like India, there are lots of pilgrims. These pilgrims gather at pilgrimage to celebrate their festival and sometime form a huge crowd. KUMBH is one of India's very largest fair event at which about 3 to 4 millions of pilgrims gather to worship their god at a time. This fair forms a huge crowd at some places like Nasik, Allahabad (Prayag), Haridwar and Ujjain. In this type of crowd, pilgrim may miss their relatives and friends. After missing it will be more complicated to find their location within the KUMBH pilgrimage premises. If Pilgrims sometimes needs emergency services like medical service then it requires some extra time to manually inform about an emergency to the authority. Pilgrims are from different regions of the country, so they require the proper information and location of the temples, rivers, hotels, hospitals, etc. Which are sometime unknown to them. Solution to these types of problem can be achieved by using technical approach. We are using passive RFID embedded wrist band to track the pilgrim within the KUMBH. Keeping the track of each pilgrim can be useful for locating the pilgrim. Pilgrim can inform about the emergency immediately using the radio frequency band available on his/her hand. Important places can be located using the application in the smart-phone like android attached with OSM (Open Street Map).

  • Online Examination with short text matching
    Pooja Kudi, Amitkumar Manekar, Kavita Daware, and Tejaswini Dhatrak
    IEEE
    In traditional Online Examination System, only objective type questions are assessed and according to that marks are given to the student. However, this technique lacks the capability of evaluating descriptive answers. In university examinations, there are many types of question included for evaluation of the students. Therefore, the automated system must be capable of evaluating the descriptive answers. The online examination system checks the student answer by matching the answer with predefined set of answer. The predefined answers are saved on the server and evaluation is done automatically using the automatic assessment tools. Here the machine learning approach is used to solve this problem using text mining. Measuring the similarity between, sentences, words, documents and paragraphs is an important component in various tasks such as text summarization, information retrieval, automatic essay scoring, document clustering, and machine translation and word-sense disambiguation. In this system JSON is used for transferring data between web application and server, serving as an alternative to XML.

  • Mining strong valid association rule from frequent pattern and infrequent pattern based on min-max sinc constraints
    Mukesh Poundekar, Amitkumar S. Manekar, Mukesh Baghel, and Hitesh Gupta
    IEEE
    Rule mining is very efficient technique for find relation of correlated data. The correlation of data gives meaning full extraction process. For the mining of rule mining a variety of algorithm are used such as Apriori algorithm and tree based algorithm. Some algorithm is wonder performance but generate negative association rule and also suffered from multi-scan problem. In this paper we proposed IMLMS-PANR-GA association rule mining based on min-max algorithm and MLMS formula. In this method we used a multi-level multiple support of data table as 0 and 1. The divided process reduces the scanning time of database. The proposed algorithm is a combination of MLMS and min-max algorithm. Support length key is a vector value given by the transaction data set. The process of rule optimization we used min-max algorithm and for evaluate algorithm conducted the real world dataset such as heart disease data and some standard data used from UCI machine learning repository.

  • Android 'Health-Dr.' application for synchronous information sharing
    Mayur S. Potdar, Amitkumar S. Manekar, and Rajesh D. Kadu
    IEEE
    Android "Health-DR." is innovative idea for ambulatory appliances. In rapid developing technology, we are providing "Health-DR." application for the insurance agent, dispensary, patients, physician, annals management (security) for annals. So principally, the ample of record are maintain in to the hospitals. The application just needs to be installed in the customer site with IT environment. Main purpose of our application is to provide the healthy environment to the patient. Our cream focus is on the "Health-DR." application meet to the patient regiment. For the personal use of member, we provide authentication service strategy for "Health-DR." application. Prospective strategy includes: Professional Authentications (User Authentication) by doctor to the patient, actuary and dispensary. Remote access is available to the medical annals, doctor affability and patient affability. "Health-DR." provides expertness anytime and anywhere. The application is middleware to isolate the information from affability management, client discovery and transit of database. Annotations of records are kept in the bibliography. Mainly, this paper focuses on the conversion of E-Health application with flexible surroundings.

  • Sifting of a potent convex hull algorithm for scattered point set using parallel programming
    Amitkumar S. Manekar, Malti Nagle, Pankaj Kawadkar, and Hitesh Gupta
    IEEE
    Geographic Information Systems (GIS) has been prominently working for the designed to sculpt the world. With the growth and data and increasing sophistication of analysis and processing techniques the traditional sequential methods of performing GIS processing on desktop computers is insufficient. This paper is based on analysis and the performance of 3D convex hull algorithm for the three flavors of parallel architecture considering spatial scatter point data using parallel programming. As GIS use huge set of scatter data for processing and development of many product, a Convex Hull of planner scattered point set will useful in the area of planning and grafting the satellite image in GIS. Analysis is based on the parallel algorithm on OpenMP, MPI and Hybrid of HPC (High Performance Computing) architecture also improvement strategy for the huge data point available for computing such as GIS spatial data with respective OpenMP, MPI and Hybrid is stated.

RECENT SCHOLAR PUBLICATIONS

  • Exploring an Immersive AR/VR Pedagogical Approach: Experiential Learning for Autism Spectrum Disorder (ASD) Education
    A Manekar, V Gade, R Unhale, H Manker, R Dhole
     2024

  • Real-Time Verification and Updates of End-of-Life (EOL) Data: Enhancing Database Maintenance through ChatGPT Integration
    G Borle, J Gore, R Dangra, A Manekar
    interactions 8, 11 2024

  • Comparative analysis of nature-inspired MetaHeuristic optimization algorithms
    AH Deshmukh, KS Kumbhare, P Jaikar, A Varma, AS Manekar
    SSGM Journal of Science and Engineering 1 (1), 169-173 2023

  • Smart information desk using raspberry pi
    A Agrawal, K Bonde, V Kanherkar, R Jadhav, A Manekar
    IJETT 9 (1) 2023

  • Python and MySQL-based Transport Management System
    N Sonkalyari, A Patil, T Zade, K Sharma, A Manekar
     2023

  • Expense Tracker Application using Naive Bayes
    R Thakare, N Thakare, R Sangtani, S Bondre, A Manekar
     2023

  • Metaheuristic Optimization Using Hybrid Algorithm in Cloud-Based Big Data Analytics
    A Manekar, G Pradeepini
    Proceedings of the 2nd International Conference on Computational and Bio 2021

  • Optimizing cost and maximizing profit for multi-cloud-based big data computing by deadline-aware optimize resource allocation
    A Manekar, G Pradeepini
    Recent Studies on Computational Intelligence: Doctoral Symposium on 2020

  • Migrating Big Data to Cloud a Hybrid Algorithm for Solving the Cost Optimization Problem
    M Amitkumar S, DG Pradeepini
    http://solidstatetechnology.us/index.php/JSST/article/view/1747 63 (5 (2020 2020

  • Advances in Computational and Bio-Engineering: Proceeding of the International Conference on Computational and Bio Engineering, 2019, Volume 1
    S Jyothi, DM Mamatha, SC Satapathy, KS Raju, MN Favorskaya
    Springer Nature 2020

  • Optimize Neutral Framework With Fair Share Resource Allocator For Big Data Processing On Cloud Infrastructure
    A Manekar, P Gera
    2019 International Conference on Innovative Trends and Advances in 2019

  • Splay: A lightweight video streaming application
    NS Inkane, SA Kotak, AS Manekar
    2019 International Conference on Innovative Trends and Advances in 2019

  • Mahaganana: An Approach to a Smart Census in India
    J Wakhariya, P Gangrade, A Manekar
    2019 International Conference on Innovative Trends and Advances in 2019

  • Trends and Advances in Engineering and Technology (ICITAET)
    MCU Wavelets
    Technology (ICITAET) 27, 28 2019

  • Studying cloud as IAAS for big data analytics: opportunity, challenges
    A Manekar, P Gera
    Int. J. Eng. Technol 7 (2.7), 909-912 2018

  • A pragmatic study and analysis of load balancing techniques in parallel computing
    V Thakur, S Kumar
    Information and Decision Sciences: Proceedings of the 6th International 2018

  • Opportunity and challenges for migrating big data analytics in cloud
    SA Manekar, G Pradeepini
    IOP conference series: materials science and engineering 225 (1), 012148 2017

  • Big data analytics: hadoop and tools
    M Sogodekar, S Pandey, I Tupkari, A Manekar
    2016 IEEE Bombay Section Symposium (IBSS), 1-6 2016

  • Cloud based big data analytics a review
    AK Manekar, G Pradeepini
    2015 International Conference on Computational Intelligence and 2015

  • Reduce Cost in Relational Domain Using a New Progressive Analytics
    AS MANEKAR
    International Conference on "Emerging Trends in Computer Engineering 2015

MOST CITED SCHOLAR PUBLICATIONS

  • Cloud based big data analytics a review
    AK Manekar, G Pradeepini
    2015 International Conference on Computational Intelligence and 2015
    Citations: 24

  • Big data analytics: hadoop and tools
    M Sogodekar, S Pandey, I Tupkari, A Manekar
    2016 IEEE Bombay Section Symposium (IBSS), 1-6 2016
    Citations: 23

  • Online Examination with short text matching
    P Kudi, A Manekar, K Daware, T Dhatrak
    2014 IEEE Global Conference on Wireless Computing & Networking (GCWCN), 56-60 2014
    Citations: 22

  • A review on cloud-based big data analytics
    A Manekar, G Pradeepini
    ICSES Journal on Computer Networks and Communication (IJCNC) 1 2015
    Citations: 14

  • A pragmatic study and analysis of load balancing techniques in parallel computing
    V Thakur, S Kumar
    Information and Decision Sciences: Proceedings of the 6th International 2018
    Citations: 13

  • Opportunity and challenges for migrating big data analytics in cloud
    SA Manekar, G Pradeepini
    IOP conference series: materials science and engineering 225 (1), 012148 2017
    Citations: 10

  • Studying cloud as IAAS for big data analytics: opportunity, challenges
    A Manekar, P Gera
    Int. J. Eng. Technol 7 (2.7), 909-912 2018
    Citations: 6

  • A novel approach to prevent personal data on a social network using graph theory
    NA Patil, AS Manekar
    2015 international conference on computing communication control and 2015
    Citations: 6

  • Android" Health-Dr." Application for Synchronous Information Sharing
    MS Potdar, AS Manekar, RD Kadu
    2014 Fourth International Conference on Communication Systems and Network 2014
    Citations: 6

  • Splay: A lightweight video streaming application
    NS Inkane, SA Kotak, AS Manekar
    2019 International Conference on Innovative Trends and Advances in 2019
    Citations: 5

  • Automated parking slot allotter using RFID and NFC technology
    H Phuse, S Bajare, R Joshi, A Manekar
    International Journal of Research in Computer & Information technology 2015
    Citations: 5

  • Mining strong valid association rule from frequent pattern and infrequent pattern based on min-max sinc constraints
    M Poundekar, AS Manekar, M Baghel, H Gupta
    2014 Fourth International Conference on Communication Systems and Network 2014
    Citations: 5

  • Optimizing cost and maximizing profit for multi-cloud-based big data computing by deadline-aware optimize resource allocation
    A Manekar, G Pradeepini
    Recent Studies on Computational Intelligence: Doctoral Symposium on 2020
    Citations: 4

  • Advances in Computational and Bio-Engineering: Proceeding of the International Conference on Computational and Bio Engineering, 2019, Volume 1
    S Jyothi, DM Mamatha, SC Satapathy, KS Raju, MN Favorskaya
    Springer Nature 2020
    Citations: 4

  • Comparative analysis of nature-inspired MetaHeuristic optimization algorithms
    AH Deshmukh, KS Kumbhare, P Jaikar, A Varma, AS Manekar
    SSGM Journal of Science and Engineering 1 (1), 169-173 2023
    Citations: 3

  • Metaheuristic Optimization Using Hybrid Algorithm in Cloud-Based Big Data Analytics
    A Manekar, G Pradeepini
    Proceedings of the 2nd International Conference on Computational and Bio 2021
    Citations: 3

  • Radio frequency based navigation and management system for KUMBH
    A Sharma, A Raut, P Donde, AK Manekar
    2015 IEEE International Conference on Computational Intelligence 2015
    Citations: 3

  • Review automated students attendance Management System using Raspberry-Pi and NFC
    NP Shegokar, S Kaustubh, M Amitkumar
    Technology (IJRCIT) 1 (1) 2015
    Citations: 3

  • Mahaganana: An Approach to a Smart Census in India
    J Wakhariya, P Gangrade, A Manekar
    2019 International Conference on Innovative Trends and Advances in 2019
    Citations: 2

  • Sifting of a Potent Convex Hull Algorithm for Scattered Point Set Using Parallel Programming
    AS Manekar, M Nagle, P Kawadkar, H Gupta
    2013 5th International Conference and Computational Intelligence and 2013
    Citations: 2