MPSTME Chronicle

 

Faculty publications

Rhea Gupta and Sara Dharadhar (Alumni Students of Computer Engineering Department) along with Prof. Prathamesh Churi published an article titled: Cloud JS: novel cloud-based design framework for text-file encryption in Emerald’s World Journal of Engineering (ESCI, Scopus). The purpose of this paper is to implement the CloudJS algorithm, to discuss its performance and compare the obtained results with existing cloud encryption schemes. The paper is found in this link: https://doi.org/10.1108/WJE-04-2021-0234

Rajni Aron (Data Science Department) has published as an article "A Novel Visual-Textual Sentiment Analysis Framework for Social Media Data" in Journal of Cognitive Computations, Springer Netherlands (Science Citation Index Expanded (SciSearch), DBLP, Scopus) with an Impact factor of 5.418. The article proposed a new VIsual-TExtual Sentiment Analysis (VITESA) framework that carries out visual analysis and textual analysis for polarity classification. In the VITESA framework, Brownian Movement-based Meerkat Clan Algorithm-centered DenseNet (BMMCA-DenseNet) is proposed that integrates textual and visual information for robust sentiment analysis. https://doi.org/10.1007/s12559-021-09929-3

Sahajanand Kamat and Meenal Mategaokar (Civil Engineering Department) with Mrunalini Sambhare (Mithibai College) has published a paper titled "In Situ Bioremediation of Phenol through Confined Aquifer Using Mesh-Free Point Collocation Method with Radial Basis Function" in ASCE Journal of Hazardous, Toxic, and Radioactive Waste. (Scopus, ESCI Web of Science). The paper focused on bioremediation modeling of phenol as a contaminant in groundwater aquifer. The ASCE Library Link for the paper is: https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HZ.2153-5515.0000658

Payal B. Joshi (BSH Department, MPSTME) published an Indian patent (Application Number: 202121048702) titled, ‘A Crop health monitoring system using machine learning,’ on 10th Dec 2021. The work involves the detection of plant-based severe diseases using advanced machine learning techniques, optimization techniques, and automated chemical analysis. For more details, visit: https://ipindiaservices.gov.in/publicsearch

Mahesh Kale and Minirani S (BSH Department - Mathematics) published a research article titled “Bounds for fuzzy Zagreb Estrada index” in the Journal “Communications in Combinatorics and Application” (Scopus). In this paper, the authors introduce the Zagreb Estrada index of fuzzy graphs and establish its bounds. http://comb-opt.azaruniv.ac.ir/article_14326.html

Prathamesh Churi (Department of Computer Engineering) co-authored an article titled Hybridizing Convolutional Neural Network for Classification of Lung Diseases in the IGI Global’s International Journal of Swarm Intelligence Research (Scopus, ESCI). Pulmonary disease is widespread worldwide. There is persistent blockage of the lungs, pneumonia, asthma, TB, etc. It is essential to diagnose the lungs promptly. For this reason, machine learning models were developed. Many deep learning technologies, including CNN and the capsule network, are used for lung disease prediction. The fundamental CNN has low rotating, inclined, or other irregular image orientation efficiency. Therefore, by integrating the space transformer network (STN) with CNN, we propose a new hybrid deep learning architecture named STNCNN. The new model is implemented on the dataset from the Kaggle repository for an NIH chest X-ray image. STNCNN has an accuracy of 69% in respect of the entire dataset. The paper can be found at:https://www.igi-global.com/article/hybridizing-convolutional-neural-network-for-classification-of-lung-diseases/287544

Patent

An Indian patent was granted to Dr. Manoj Sakharam Sankhe (Department of Electronics and Telecommunication Engineering) for an invention entitled ‘A Novel Technique for Assessment of Fetal Autonomic Nervous System Activity from Doppler Ultrasound Signal’ for the term of 20 years from 29th June, 2015 by the Government of India (Patent Number: 2474/MUM/2015). The invention relates to a novel efficient technique for processing the Doppler ultrasound signal, which could estimate the cardiac cycle duration with accuracy comparable to direct electrocardiography. This study also relates to a computer-based analytical system to find the heart rate and analyze it to obtain HRV Power-spectrum for investigation of the autonomic nervous system (ANS) during fetal gestational development.

Events organized in MPSTME

Department of Electronics and Telecommunication Engineering, Dr. Alka Mahajan, Dean, Convener, Dr. Manoj Sankhe, Coordinator, Prof. Kashyap Joshi and Prof. Punit Ratnani, Co-coordinator organized an AICTE-ISTE Sponsored One Week Online Refresher Program on “Future Trends in Biomedical Engineering”. This program was designed to provide insights to participants for developing applications in Biomedical Engineering by focusing on recent trends & case studies. The program was focused on engineering models to provide solutions to meet specific needs while considering public health, safety, and welfare, as well as global, environmental, and economic factors, and helped participants to recognize ethical and professional responsibilities in providing engineering solutions in medical fields.

Award and Achievements

MPSTME, Mumbai received an award of Top Emerging Institute by Times Education Icons, Mumbai 2021. This award has been felicitated based on Times Engineering Survey 2021

MPSTME, Mumbai Students Ayan Ray, Hrishita Goyal, Katyayani Nath, Naitik Udeshi, Rishabh Dubey, Yash Chopra (Computer Engineering and IT Department) have made it to ET Campus Stars Class of 2021. The fourth edition of ET Campus Stars aimed to identify India’s brightest engineers poised to shape the future of the nation in various fields of engineering.

MPSTME Students Akshada Gaonkar, Prerit Gupta, Yash Gupta, mentored by Prof. Dattatray Sawant, won Best Paper Award in third place at IEEE Bombay Section Signature Conference (IBSSC-2021) organized by IEEE Bombay Section and ABV-IIITM Gwalior, India.  Their paper title was "Anti-CoVi-Bot: A Robot to Combat COVID-19.