Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) Lentera Hukum Journal of Applied Pharmaceutical Research
Sharma, Manoj Kumar
Unknown Affiliation
Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Deep convolutional neural network framework with multi-modal fusion for Alzheimer’s detection Sharma, Manoj Kumar; Kaiser, M. Shamim; Ray, Kanad
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i1.pp179-191

Abstract

The biomedical profession has gained importance due to the rapid and accurate diagnosis of clinical patients using computer-aided diagnosis (CAD) tools. The diagnosis and treatment of Alzheimer’s disease (AD) using complementary multimodalities can improve the quality of life and mental state of patients. In this study, we integrated a lightweight custom convolutional neural network (CNN) model and nature-inspired optimization techniques to enhance the performance, robustness, and stability of progress detection in AD. A multi-modal fusion database approach was implemented, including positron emission tomography (PET) and magnetic resonance imaging (MRI) datasets, to create a fused database. We compared the performance of custom and pre-trained deep learning models with and without optimization and found that employing natureinspired algorithms like the particle swarm optimization algorithm (PSO) algorithm significantly improved system performance. The proposed methodology, which includes a fused multimodality database and optimization strategy, improved performance metrics such as training, validation, test accuracy, precision, and recall. Furthermore, PSO was found to improve the performance of pre-trained models by 3-5% and custom models by up to 22%. Combining different medical imaging modalities improved the overall model performance by 2-5%. In conclusion, a customized lightweight CNN model and nature-inspired optimization techniques can significantly enhance progress detection, leading to better biomedical research and patient care.
Isolation and characterization of cellulose derived from prominent agricultural waste (Sugarcane bagasse) and its utilization in various biomedical field Sharma, Manoj Kumar; Diwan, Anupama; Sardana , Satish; Yadav, Narender; Gupta, Tanya; Kumawat , Mukesh Kumar
Journal of Applied Pharmaceutical Research Vol. 13 No. 1 (2025)
Publisher : Creative Pharma Assent

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69857/joapr.v13i1.942

Abstract

Background: Agricultural waste clearance and reutilization is a significant problem today. Objective: Successful extraction and purification of cellulose and its derivatives (methylcellulose) from agri-waste and pollution. This is an innovative polymer (cellulose & its derivatives) that can be used in pharmaceutical and technical applications in an eco-friendly manner. Aim: Isolate and characterize cellulose derived from prominent agricultural waste (sugarcane bagasse) and its utilization in various biomedical fields. Method: Eco-friendly Soxhlet extraction utilizing organic solvents was employed to give a high yield of cellulose. Further, the obtained cellulose was bleached and transformed into ester derivatives, such as methylcellulose, to analyze their properties. Result: This study’s primary goal is to concentrate on the production of cellulose and its extraction from different agricultural waste & its characterization. The cellulose isolated from different biomass was comparatively evaluated for its varied properties and was found suitable for use in the pharmaceutical industry or technical dimensions. Conclusion: Agri waste has significant potential and sources for value-based products. Here, successful extraction and derivatization of the cellulose from the sugarcane were done. These extracted celluloses were further subjected to various pharmacopeial, micromeritics, and physiochemical properties assessments, including advanced characterization to evaluate and validate the properties of the products, which signifies more efficient, green extraction and pharmacopeial utilization.
Constitutional and Legal Landscape of Right to Be Forgotten in India Sharma, Manoj Kumar; Kaur, Prabhjot
Lentera Hukum Vol. 12 No. 2 (2025): LENTERA HUKUM
Publisher : University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/ejlh.v12i2.50274

Abstract

The right to be forgotten has emerged as an important right in the internet era, where on one hand information multiplies almost every day and on the other hand, the information appears to be preserved eternally. The presence of huge amounts of information in the public domain, particularly personal information, raises concerns about privacy in the digital era where sensitive information is often retained in the public domain, at times without consent of the data holder. When examined from the perspective of criminology and penology, the availability of information in the public domain about the past behavior of people adversely affects the chances of rehabilitation and reformation due to societal taboos. This raises an important question as to why one should suffer because of their past acts, thus underscoring the importance of the right to be forgotten. This paper traces the evolution and contours of the right to be forgotten in the European Union, the UK, the USA, and India, highlighting challenges in its implementation and recognition. The constitutional and legislative measures to recognize and enforce this right have also been examined in the light of judicial decisions. Keywords: Right to be Forgotten (RTF), Right to Privacy, Court, Constitution, Data.
Co-Authors Anupama Diwan, Anupama Gupta, Tanya Kaiser, M. Shamim Kaur, Prabhjot Kumawat , Mukesh Kumar Ray, Kanad Sardana , Satish Yadav, Narender