Dr. Vinayak Dagadu Shinde

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Hardware and Architecture, Software, Computer Networks and Communications

Scopus Publications

Analyzing the Effects of K-Means and Random Forest Algorithms on Resume Classification through Manipulation of Cluster Sizes and Datasets
Sweety Mahesh Patil and Vinayak D. Shinde
IEEE
In online job recruitment, precise job classifications are crucial for both job seekers and recruiters. Categorizing resumes is a crucial stage in the multi-step recruitment process. The success of an organization heavily relies on the personality of its candidates. This system is based on two modules. Questionnaires in the MCQ format are used in Module 1 to collect input from user. Module 1 includes pre-processing using min-max scaling, enrichment using cluster optimization technique, pattern recognition using k-means clustering algorithm, and by changing the cluster’s size, personality traits can be identified and personality traits predicted. The output of Module 1 is detecting appropriate personality based on categories are Extroversion, Neuroticism, Agreeableness, Conscientiousness and Openness. When appropriate category of personality is detected in Module 1, which will be helpful in further analysis of job, resume will be passed to the system as input in PDF format to Module 2. Module 2 is based on two stages. Data collection, text vectorization on training datasets, and job title encoding are all included in stage one. Stage 2 involves input resumes in PDF format using the PyPDF2 library. The NLTK library and regular expression are used to pre-process resumes, followed by TF-IDF vectorization and Random Forest Algorithm to classify them based on similarity to job title. Accurate resume classification can be achieved by optimizing K-Means and Random Forest Algorithms, yielding a 70% accuracy rate. Ensemble learning techniques or Linear Support Vector Classifier (SVC) can potentially enhance accuracy.


Enhancing Breast Cancer Detection: A Machine Learning Approach for Early Diagnosis and Classification
Aditi Sawant, Divya Patil, Dimple Khuman, Yogesh Pingle, and Vinayak Shinde
IEEE
Millions of new cases of breast cancer are discovered worldwide each year, which is a serious health risk. For treatment options to be directed and patient outcomes to be improved, a timely and correct diagnosis is essential. Medical diagnostics has shown machine learning, and more specifically logistic regression, to be a useful tool. This work uses a logistic regression model to show how machine learning may be used practically to categorize breast cancer cases. The main goal is to develop a model that can reliably classify breast tissue as benign, malignant, or normal based on medical photos in order to aid in the early diagnosis of cancer. By reducing reliance on arbitrary human judgements, this method aims to improve the consistency and effectiveness of the diagnostic procedure.


Improved Crop Yields and Resource Efficiency in IoT-based Agriculture with Machine Learning
Santosh Kumar, Vinayak Dagadu Shinde, Uma Bhavin Goradiya, Aabha Amey Patil, Sonu Prasad Verman, and Vilas Kisanrao Tembhurne
IEEE
Despite popular belief, agricultural research today is more based on hard evidence; exact; precise, and rigorous than ever before. Almost every industry has been disrupted by the spread of IoT-based technologies, including urban planning, healthcare, the electricity grid, the home, and agriculture, frequently referred to as “smart agriculture”. Machine learning (ML) and IoT data analytics in agriculture can boost crop yields to meet rising food demand. These revolutionary developments are upending standard agricultural practices and giving rise to new and finest opportunities, but with some drawbacks. Optimal agriculture output requires this research seeks to develop an effective and precise system that uses Crop selection choices made using algorithms that utilize Internet of Things (IoT) sensors and ML Therefore, this paper, proposed an ensemble model using machine learning for crop prediction based on IoT data which is collected from the IoT sensors using the PLX-DAQ tool. There are several suggested machines learning models, including “Naive Bayes, Decision Tree, Random Forest Support Vector Machine, and K-Nearest Neighbour,”. According to the experimental findings, ensemble learning had the greatest accuracy of 97.45% for predicting early crop yields. The results of this research will significantly increase the dependence on data for choices relating to climate change and agricultural practices.







IoT-based Air Pollution Monitoring System to Measure Air Quality on Cloud Storage
Vilas Kisanrao Tembhurne, Vinayak Dagadu Shinde, Santosh Kumar, Manish Shrimali, Gunjan Chhabra, M N Quadri, and Vikram Rajpoot
IEEE
Air pollution (AP) is today’s most pressing issue. Particularly concerning are the potential adverse effects that an excessive amount of certain hazardous gases, such as CO, SO2, particulate matter, and several others, may have on human health. Other environmental gases are affected by temperature, humidity, etc., wind speed, and their causes and impacts. These weather factors include temperature, humidity, as well as wind speed.For this project, a centralized cloud-based system using sensors that monitor and analyze AP will be developed. The information gathered by each sensor node is uploaded to a cloud server, where it is stored and can be viewed through a web browser at any time and from any location. Because the environment is being monitored in real-time, prompt action may be performed in response to discovering a contaminant in the ecosystem. This project aims to monitor the AP of the surrounding area and ensure that data are kept up to date on the internet. Readings are conducted continuously throughout the day and in real-time. Many air pollutants like SO2, CO, PM10, humidity, and temperature are considered to measure air quality by IoT-based air pollution monitoring systems (APMS). We created graphics that simplify analyzing the proportion of pollutants in a certain location. The LCD can show the gas sensor’s real-time data constantly.


Alphanumeric database security through digital watermarking
Akshata A. Churi and Vinayak D. Shinde
IEEE
As the demand of online data availability increases for sharing data, business analytics, security of available data becomes important issue, data needs to be protected from unauthorized access as well as it needs to provide authority that the data is received from a trusted owner. To provide owners identity digital watermarking technique is used since long time for multimedia data. This paper proposed a technique which supports watermarking on database as most of the data available today is in database format. The characters to be entered as watermark are converted into binary values; these binary values are hidden in the database using space character. Each bit is hidden in each tuple randomly. Ant colony optimization algorithm is proposed to select tuples where watermark bits are inserted. The proposed system is enhanced in terms of security due to use of ant colony optimization and resilient because even if some bits are modified the hidden text remains almost same.


Recommendation system using content filtering: A case study for college campus placement
Nishigandha Karbhari, Asmita Deshmukh, and Vinayak D. Shinde
IEEE
Recommender system known as information gathering system aims at creating an algorithm which, keeps in consideration the diverse needs and varying level of competence. It offers better opportunities in project development cycle under requirement phase and design phase. Social media and Ecommerce market has tapped in the recommender system to boost its growth by providing with precise results. It provides with either service or product recommendation using the information gathered in the software engineering process. It is broadly divided in three categories which are Collaborative, Content-based and Hybrid recommendation approach. This paper presents a model to generate recommendations based on marks of student. It discovers best solutions which would have otherwise remained hidden. The case study performed on the recommender system implementation in college campus will result a recommendation in placement of students (employee) to companies (employer) as per their requirements in shortest possible time. It can be expected as a situation where we have tried to achieve the results while keeping in mind the requirements of employer and employee.

RECENT SCHOLAR PUBLICATIONS

Measurement of Human Attention levels using Artificial Intelligence Pattern Simulation
K Pimparkhede, VD Shinde
Solid State Technology 64 (2), 7352-7355 2021



Service Discovery Mechanism Using Dynamic Analysis
K Pimparkhede, VD Shinde
Solid State Technology 64 (2), 6557-6564 2021



PERFORMANCE ANALYSIS SYSTEM USING WEB BASED SOLUTION FOR MCQ TYPE ONLINE EXAMINATION
J Navik, A Sawant, S Saini, VD Shinde
Open Access International Journal of Science Engineering (OAIJSC-2021) 2021



client side and Server Side Load balancing
K Pimparkhede
International Journal for Research in Ap-plied Science and Engineering 2021



Measurement of Human Attention levels using Artificial Intelligence Pattern Simulation
VDS Kunal Pimparkhede
Solid State Technology 64 (2), 3461-3465 2021



alphanumeric database security through digital watermarking
AA Churi, VD Shinde
2020 International Conference on Convergence to Digital World - Quo Vadis 2020



Performance evaluation of various supervised machine learning algorithms for diabetes prediction
JR Raut, Y Sharma, VD Shinde
European Journal of Molecular & Clinical Medicine 7 (8), 2020 2020



Human Identification Using Motion Vector Analysis
C D'Souza, S Gaikwad, V Shinde
International Journals of Multi-Dimensional Research 7 (5), 1-7 2019



Traffic rules violation system using NFC card
R Yadav, A Korgaonkar, S Yadav, P Yadav, VD Shinde, S Sal
International Research Journal of Engineering and Technology (IRJET) 2018



Smart Locker Management System Using IoT
P Parab, M Kulkarni, V Shinde
system 8 (10) 2018



Recommendation system using content filtering: A case study for college campus placement
N Karbhari, A Deshmukh, VD Shinde
2017 International conference on energy, communication, data analytics and 2017



A Study on Gait Analysis for Human Identification
C D’Souza, S Gaikwad, V Shinde
International Conference On Emanations in Modern Technology and Engineering 2017



A survey on: Sound source separation methods
MMR Pimpale, S Therese, V Shinde
International Journal 3 (11), 580-584 2016



The adoption of cloud computing technologyin engineering Colleges in mumbai concern resistances and challenges
V Shinde
Jhunjhunu 2016



Generating Honeywords from Real Passwords with Decoy Mechanism
MK Naik, V Bhosale, VD Shinde
International Journal for Research in Engineering Application & Management 2 2016



Design and Implementation of Embedded Web Server and DACS with ARM9 using Linux
N Priyanka, VD Shinde
International Journal of Scientific and Research Publications, 603 2015



Survey on Distributed Incomplete Pattern Matching
MJS Pande, JW Bakal, MV Shinde
International Journal of Global Technology Initiatives 4 (1), C11-C17 2015



Design and development of ARM9 based embedded web server
N Priyanka, VD Shinde
Int. Journal of Engineering Research and Applications 5 (8), 50-53 2015



Study of cluster, grid and cloud computing
V Shinde, A Shaikh, CD D’Souza
International Journal of Advanced Research in Computer and Communication 2015



Survey on malware detection techniques
P Gaikwad, D Motwani, V Shinde
International Journal of Modern Trends in Engineering and Research 21 (7), 1-25 2015

MOST CITED SCHOLAR PUBLICATIONS

Recommendation system using content filtering: A case study for college campus placement
N Karbhari, A Deshmukh, VD Shinde
2017 International conference on energy, communication, data analytics and 2017
Citations: 29



A survey on: Sound source separation methods
MMR Pimpale, S Therese, V Shinde
International Journal 3 (11), 580-584 2016
Citations: 10



Performance evaluation of various supervised machine learning algorithms for diabetes prediction
JR Raut, Y Sharma, VD Shinde
European Journal of Molecular & Clinical Medicine 7 (8), 2020 2020
Citations: 6



Design and development of ARM9 based embedded web server
N Priyanka, VD Shinde
Int. Journal of Engineering Research and Applications 5 (8), 50-53 2015
Citations: 5



client side and Server Side Load balancing
K Pimparkhede
International Journal for Research in Ap-plied Science and Engineering 2021
Citations: 4



Survey on malware detection techniques
P Gaikwad, D Motwani, V Shinde
International Journal of Modern Trends in Engineering and Research 21 (7), 1-25 2015
Citations: 4



Smart Locker Management System Using IoT
P Parab, M Kulkarni, V Shinde
system 8 (10) 2018
Citations: 2



Study of cluster, grid and cloud computing
V Shinde, A Shaikh, CD D’Souza
International Journal of Advanced Research in Computer and Communication 2015
Citations: 2



PERFORMANCE ANALYSIS SYSTEM USING WEB BASED SOLUTION FOR MCQ TYPE ONLINE EXAMINATION
J Navik, A Sawant, S Saini, VD Shinde
Open Access International Journal of Science Engineering (OAIJSC-2021) 2021
Citations: 1



alphanumeric database security through digital watermarking
AA Churi, VD Shinde
2020 International Conference on Convergence to Digital World - Quo Vadis 2020
Citations: 1



Traffic rules violation system using NFC card
R Yadav, A Korgaonkar, S Yadav, P Yadav, VD Shinde, S Sal
International Research Journal of Engineering and Technology (IRJET) 2018
Citations: 1



A Study on Gait Analysis for Human Identification
C D’Souza, S Gaikwad, V Shinde
International Conference On Emanations in Modern Technology and Engineering 2017
Citations: 1



Generating Honeywords from Real Passwords with Decoy Mechanism
MK Naik, V Bhosale, VD Shinde
International Journal for Research in Engineering Application & Management 2 2016
Citations: 1



Design and Implementation of Embedded Web Server and DACS with ARM9 using Linux
N Priyanka, VD Shinde
International Journal of Scientific and Research Publications, 603 2015
Citations: 1



Malicious user detection using honeyword and IP tracking
MK Naik, V Bhosale, VD Shinde
International Conference On Emanations in Modern Technology and Engineering
Citations: 1



Government policies search using marathi speech recognition system-based on mfcc with gamma-tone filter
M Parande, S Therese, V Shinde

Citations: 1