Social Networks Analysis
Internet of Things
Time Series Analysis
Recommendation System
Machine Learning
150
Scopus Publications
154
Scholar Citations
7
Scholar h-index
5
Scholar i10-index
Scopus Publications
Geospatial analysis of land use and land cover change and environmental impacts in Uttarakhand, India: A review Mohammad Aves, Manish Sharma, Hemant Singh Pokhariya Environmental and Sustainability Indicators, 2026 Uttarakhand, Himalaya's a state, is having serious environmental problems that are mainly due to urbanization, infrastructure development, and climate change. The systematic review gathers together geospatial studies in order to assess the extent of LULC changes and their impact on the environment. Following PRISMA 2020 rules, we went through more than 150 records and finally picked 30 peer-reviewed papers from 2021 to 2025 for the in-depth synthesis based on the quality of the methodology and geographic relevance. The review shows a clear movement in the methods of remote sensing from parametric classifiers to machine learning algorithms (Random Forest, SVM) and cloud computing (Google Earth Engine). The quantitative synthesis indicates a stark contrast in development trends: the plains and foothills (Dehradun, Haridwar, Udham Singh Nagar) are experiencing rapid urban-industrial development, with built-up areas in some places like Haridwar increasing more than 200%, causing very strong urban heat island effects and even more stressed groundwater. On the other hand, mid-hills and high Himalayas (Pauri, Almora, Chamoli) are suffering from agricultural abandonment, forest fragmentation, landslides due to infrastructure, and the like. The review points out that even though there is high-accuracy geospatial data, there is still a "knowledge-to-action" gap in the governance of the state where scientific knowledge is seldom referred to in master planning or disaster risk reduction frameworks. • Uttarakhand’s land use is rapidly changing, with forests and farms giving way to built-up areas. • Advanced machine learning and cloud-based GIS techniques yield the most accurate land cover maps. • Urban growth is increasing heat and hazard exposure across the region. • Despite strong scientific evidence, geospatial insights are not yet fully used in planning policy.
Two-Dimensional Simulation of Generalized Thermoelastic Damping in Vibrations of Strain Gradient Beam Resonators Wade Ghribi, Pinank Patel, M. K. Ranganathaswamy, Rohit Sharma, Sabir Widatalla, Vikasdeep Singh Mann, Marwa Alhedrawe, Ankit Kedia, M. K. Sharma, Abhinav Kumar International Journal of Structural Stability and Dynamics, 2026 The operation of micro/nanobeam resonators is greatly impacted by the thermoelastic damping (TED) phenomenon, highlighting the need for precise determination of its value. Given the confirmed size effects in both mechanical and thermal fields, along with the importance of utilizing the two-dimensional (2D) heat transfer model over the 1D model for more accurate simulation of the thermomechanical behavior of small-scale beams, this paper aims, for the first time, to present a 2D model for TED using the modified strain gradient theory (MSGT) and the nonlocal dual-phase-lag (NDPL) heat equation. To accomplish this, the 2D NDPL-based temperature distribution is calculated using the Galerkin method, while the MSGT is applied to determine the size-dependent constitutive equations. The obtained relations are then used in the energy dissipation (ED) method to derive a TED formula in the form of infinite series. To validate the model’s accuracy, a simplified version is employed for comparison. A detailed convergence study is also performed to determine the optimal number of terms needed for precise results. Finally, a thorough parametric analysis is undertaken to explore how key factors like 2D heat transfer and non-classical constants in the MSGT and NDPL model impact TED. The findings highlight the importance of using the MSGT and NDPL model in micro- and sub-micro dimensions, and the need for the 2D model in beams with low aspect ratios.
Automated Breast Cancer Diagnosis from Ultrasound Using Vision-Eagle Attention Narinder Kaur, Prabh Deep Singh, Kiran Deep Singh, Manish Sharma, Dipannita Ray, Sonia F Panesar Proceedings of the 12th International Conference on Biosignals Images and Instrumentation Icbsii 2026, 2026 Breast cancer has always been one of the most significant causes of deaths in the female population across the world with early and precise diagnosis being a major factor in increasing the survival chances. Ultrasound imaging is popular in the detection of breast lesions, but detection by hand is difficult because of speckle noise, low contrast, and large intraclass variability. In this paper, the authors suggest a new deep learning model that incorporates EfficientNetV2L with a Vision-Eagle-Attention (VEA) system to classify cancer in the breast using automated systems. The attention module proposed fuses global contextual awareness with channel and spatial feature refinement in order to boost discriminative representation of ultrasound images. There was an experiment on the BUSI breast ultrasound dataset which had benign, malignant and normal classes. The experiments were done on the BUSI data that had benign, malignant, and normal classes. The proposed model had a general classification accuracy of 92 % with high rates of evaluation indicated by high rates of precision, recall and F1-score of all the classes. The findings show that it converges stably, has high ROC property, and enhances generalization. The suggested EfficientNetV2L-VEA framework has a potential to be an effective computer-aided diagnosis system that can be used to detect breast cancer in the initial stage and reliably.
Sparse Combination of Mixture of Experts: An Optimized Text Classification Approach for Natural Language Processing Ashish Prasad, Manish Sharma, Mohit Singh 2025 International Conference on Intelligent and Secure Engineering Solutions Cises 2025, 2025 Processing in the field of NLP which has seen applications in the area of. News category assignment, sentiment analysis, and info retrieval. Despite in the ability of transformer models such as to perform. As BERT what we see is that their architecture is very large and dense out. High computational resources and poor scalability. To address these. Issues we present a Sparse Combination of Mixture of. Experts (SC-MoE) model which utilizes the large context of. Formation that BERT puts forth and also in which it includes dynamically. Routed out of the box (OOB) which is a type of Mix of Experts (MoE) architecture. In what we have designed as a two stage approach the lower BERT layers are left frozen to preserve the pre trained features, at the same time the final sentence embedding is put through a few specialized experts. This we did to maximize on deep semantic meaning at the same time present a more efficient solution. We looked at the AG News dataset which SC-MoE was evaluated on and we achieved 94.56 % accuracy which we see to out perform state of the art methods like RSS-LSTM (91.00%, SECNN (90.54% and contrastive loss based CNN models (88.02%. The model shows consistent performance on the four topic classes, World, Sports, Business, and Sci/Tech, in addition to removing computational redundancy through selective expert activation. In addition, we combine token-level interpretability analyses, such as attention-based visualization, to gain insight into how SC-MoE dynamically distributes attention over relevant terms. These findings highlight SC-MoE’s success as a scalable, high-performance substitute for monolithic transformer models for real-world text classification problems.
Emerging Evidence for Association of Transsulfuration Pathway with Hypoxia Responses Neha Jain, Manish Sharma Defence Life Science Journal, 2024 When people ascend to a high altitude (HA), the body’s oxygen (O2) sensing mechanisms can sense perturbation in partial pressure and trigger adaptive responses. Rapid ascending to HA without ample time for acclimatization culminates in high-altitude illnesses, which can derail the body functioning of lowlanders moving to HA. High-altitude native populations have undergone positive natural selection to efficiently overcome the challenges of chronic hypobaric hypoxia (HH) and thus offer a unique model to understand physiological and genetic adaptations at high altitudes. In addition, evolutionary shreds of evidence propose that sulfur belonging to the same periodic table family can mimic oxygen to bypass its metabolic oxygen demand and modulate energy production.Intriguingly, our group has identified a strong association between diminished hydrogen sulfide (H2S)levels and HH-induced pathological responses. We have recently presented experimental evidence of cysteine deficit, which functionally regulates both lowered levels of endogenous H2S and HH-induced neuropathological responses. In this review, we sought to understand the role of H2S and the transsulfuration pathway at HA.
Optimizing Computed Tomography Image Reconstruction Parameters for Improved Lung Cancer Diagnosis with Grey Wolf Algorithm International Journal of Intelligent Systems and Applications in Engineering, 2024
Applications of ultrafiltration, nanofiltration, and reverse osmosis in pharmaceutical wastewater treatment Saurabh Gupta, Anupam Singh, Tarubala Sharma, Rasanpreet Kaur, Vishal Khandelwal, Krishna Dutta Rawat, Shreya Pathak, Manish Kumar Sharma, Jitendra Singh, Maulin P. Shah, Subhash C. Chauhan, Deepak Parashar, Prem Shankar, Vivek K. Kashyap Development in Wastewater Treatment Research and Processes Innovative Trends in Removal of Refractory Pollutants from Pharmaceutical Wastewater, 2024
Pharmaceutical wastewater management Tarubala Sharma, Vishal Khandelwal, Saurabh Gupta, Anupam Singh, Rasanpreet Kaur, Shreya Pathak, Manish Kumar Sharma, Anshul Sharma, Bhuvnesh P. Sharma, Jitendra Singh, Maulin P. Shah, Subhash C. Chauhan, Deepak Parashar, Prem Shankar, Vivek K. Kashyap Development in Wastewater Treatment Research and Processes Innovative Trends in Removal of Refractory Pollutants from Pharmaceutical Wastewater, 2024
Brain tumor detection using deep learning Waqar Ahamad, Vipul Pal, Shreyash, Manish Kumar Sharma Proceedings IEEE 2023 5th International Conference on Advances in Computing Communication Control and Networking Icac3n 2023, 2023
Classification of Various Cloud Attacks using Machine Learning Techniques Disha Chauhan, Aman Kumar Chauhan, Amit Gupta, Richa Gupta, Manish Sharma 2023 International Conference on the Confluence of Advancements in Robotics Vision and Interdisciplinary Technology Management IC Rvitm 2023, 2023
An Insight Through Reviews on Neural Network Based Data Mining Aasheesh Shukla, Manish Sharma, A Kakoli Rao, N Shalini, Navneet Kumar, Sahil Singh, Ajay Rana Proceedings of International Conference on Contemporary Computing and Informatics Ic3i 2023, 2023
Covid-19 Detection on X-Ray Image Using Deep Learning Roja Boina, Abhay Chaturvedi, Manish Sharma, Anurag Shrivastava, Indradeep Kumar, Aln Rao 4th International Conference on Intelligent Engineering and Management Iciem 2023, 2023
Identification of Dog Breeds Using Deep Learning Rakesh Kumar, Manish Sharma, Kritika Dhawale, Gaurav Singal Proceedings of the 2019 IEEE 9th International Conference on Advanced Computing Iacc 2019, 2019
Optimizing Computed Tomography Image Reconstruction Parameters for Improved Lung Cancer Diagnosis with Grey Wolf Algorithm R Gudur, AI Tamboli, A Garg, M Sharma International Journal of Intelligent Systems and Applications in Engineering … , 2024 2024
Influence of Unbalance on Tyre Pressure Monitoring System Based on C-GRU Approach G Sivashankar, SK Prasad, A Saravanan, MV Ghamande, AR Aravind, ... 2023 7th International Conference on Electronics, Communication and … , 2023 2023 Citations: 2
Sowing the Seeds of AI in Agriculture: Federated Learning CNN for Groundnut Disease Detection V Jindal, V Kukreja, S Mehta, R Gupta, M Sharma 2023 4th IEEE Global Conference for Advancement in Technology (GCAT), 1-6 , 2023 2023 Citations: 2
The Role of Federated Learning and CNNs in the Detection and Classification of Zucchini Leaf Diseases: A Severity-Based Analysis V Jindal, V Kukreja, S Mehta, S Chamoli, M Sharma 2023 4th IEEE Global Conference for Advancement in Technology (GCAT), 1-6 , 2023 2023 Citations: 1
Harmonizing Nature and Technology: CNN-SVM for Cercospora Leaf Spot Disease Recognition in Chilli Plants A Kaur, V Kukreja, R Yadav, S Tanwar, M Sharma 2023 4th IEEE Global Conference for Advancement in Technology (GCAT), 1-6 , 2023 2023 Citations: 2
Detection of Behavioral Patterns of Viral Hepatitis Using Data Mining VG Shende, A Jency, K Pavithra, T Jayasudha, G Venkatesan, M Sharma 2023 4th International Conference on Smart Electronics and Communication … , 2023 2023 Citations: 1
Tackling Agricultural Challenges of Red Globe Grapes Leaf Diseases: A Federated Learning CNN Approach V Jindal, V Kukreja, S Mehta, A Gupta, M Sharma 2023 3rd Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2023 2023 Citations: 12
An Efficient Approach For To Predict The Quality Of Apple Through Its Appearance D Goel, D Singh, A Gupta, SP Yadav, M Sharma 2023 International Conference on Computer, Electronics & Electrical … , 2023 2023 Citations: 31
An Investigation on the Mathematical Models for the Growth of Some Tumor Cells and Their Control M Sharma, SK Pandey International Journal of Scientific Research in Modern Science and … , 2023 2023
Covid-19 Detection on X-Ray Image Using Deep Learning R Boina, A Chaturvedi, M Sharma, A Shrivastava, I Kumar, A Rao 2023 4th International Conference on Intelligent Engineering and Management … , 2023 2023 Citations: 1
Trs: Trusted recommendation system for fast changing dataset M Sharma, B Pant, V Singh AIP Conference Proceedings 2521 (1) , 2023 2023 Citations: 1
The Significance of using Data Extraction Methods for an Effective Big Data Mining Process M Sharma, R Gupta 2023 2nd International Conference for Innovation in Technology (INOCON), 1-4 , 2023 2023 Citations: 12
Development of IoT based Health Monitoring System for Disables using Microcontroller R Josphineleela, M Jyothi, L Natrayan, A Kaviarasu, M Sharma 2023 7th International Conference on Computing Methodologies and … , 2023 2023 Citations: 18
Digital Dimensions: Unveiling the Potential of E-Design and Virtual Prototyping K Yadav, S Chirade, M Banerjee, M Sharma, NS Ramya, K Aravinda, ... E3S Web of Conferences 453, 01031 , 2023 2023 Citations: 6
A millimeter wave filter for 5g applications PK Sharma, A Rana, S Sharma, M Sharma, M Mengstie, AT Rao 2022 5th International Conference on Contemporary Computing and Informatics … , 2022 2022 Citations: 1
Environmental flow monitoring system–the need of the hour M Sharma, C Prakasam, R Saravanan, VS Kanwar, MK Sharma, SC Attri AIP Conference Proceedings 2451 (1) , 2022 2022
Achieving the LDL-C goal in Indian patients of acute coronary syndrome with high intensity statin J Sawhney, JG Vanani, K Madan, MK Sharma, K Tyagi, B Kandpal, ... Atherosclerosis 355, 107 , 2022 2022
Assessing and Correlating the Flow Duration Curve and Drought Index for the Environmental Flow Requirements C Prakasam, R Saravanan, VS Kanwar, MK Sharma Proceedings of International Conference on Innovative Technologies for Clean … , 2022 2022
Combination of data mining and artificial intelligence algorithms for efficient web page recommendation M Sharma International Journal of Health Sciences 6 (S3), 2532-2546 , 2022 2022
Lipoprotein (a) in young coronary artery disease and its association with severity of coronary artery disease JPS Sawhney, K Tyagi, MK Sharma, K Madan, JK Vanani, B Kandpal, ... Atherosclerosis 331, e117 , 2021 2021
MOST CITED SCHOLAR PUBLICATIONS
An Efficient Approach For To Predict The Quality Of Apple Through Its Appearance D Goel, D Singh, A Gupta, SP Yadav, M Sharma 2023 International Conference on Computer, Electronics & Electrical … , 2023 2023.0 Citations: 31
Development of IoT based Health Monitoring System for Disables using Microcontroller R Josphineleela, M Jyothi, L Natrayan, A Kaviarasu, M Sharma 2023 7th International Conference on Computing Methodologies and … , 2023 2023.0 Citations: 18
Demographic profile building for cold start in recommender system: A social media fusion approach M Sharma, B Pant, V Singh Materials Today: Proceedings 46, 11208-11212 , 2021 2021.0 Citations: 18
Tackling Agricultural Challenges of Red Globe Grapes Leaf Diseases: A Federated Learning CNN Approach V Jindal, V Kukreja, S Mehta, A Gupta, M Sharma 2023 3rd Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2023 2023.0 Citations: 12
The Significance of using Data Extraction Methods for an Effective Big Data Mining Process M Sharma, R Gupta 2023 2nd International Conference for Innovation in Technology (INOCON), 1-4 , 2023 2023.0 Citations: 12
Review on: content based image retrieval A Purbey, M Sharma, B Bohra International Journal of Scientific & Engineering Research 8 (1), 510-513 , 2017 2017.0 Citations: 7
A Survey of project scenario impact in SDLC models selection process M Sharma International Journal of Scientific & Engineering Research 2 (7), 1-4 , 2011 2011.0 Citations: 7
Digital Dimensions: Unveiling the Potential of E-Design and Virtual Prototyping K Yadav, S Chirade, M Banerjee, M Sharma, NS Ramya, K Aravinda, ... E3S Web of Conferences 453, 01031 , 2023 2023.0 Citations: 6
STP: Suicidal Tendency Prediction Among the Youth Using Social Network Data M Sharma, B Pant, V Singh, S Kumar Next Generation Information Processing System, 161-169 , 2020 2020.0 Citations: 6
Effect of growth substances on morpho-physiological traits and yield in pearl millet under rainfed condition GM Parmar, PR Patel, SK Parmar, KD Mungra, MK Sharma Journal of Pharmacognosy and Phytochemistry 10 (2), 971-974 , 2021 2021.0 Citations: 3
Influence of Unbalance on Tyre Pressure Monitoring System Based on C-GRU Approach G Sivashankar, SK Prasad, A Saravanan, MV Ghamande, AR Aravind, ... 2023 7th International Conference on Electronics, Communication and … , 2023 2023.0 Citations: 2
Sowing the Seeds of AI in Agriculture: Federated Learning CNN for Groundnut Disease Detection V Jindal, V Kukreja, S Mehta, R Gupta, M Sharma 2023 4th IEEE Global Conference for Advancement in Technology (GCAT), 1-6 , 2023 2023.0 Citations: 2
Harmonizing Nature and Technology: CNN-SVM for Cercospora Leaf Spot Disease Recognition in Chilli Plants A Kaur, V Kukreja, R Yadav, S Tanwar, M Sharma 2023 4th IEEE Global Conference for Advancement in Technology (GCAT), 1-6 , 2023 2023.0 Citations: 2
Studies on Organic Nutrient Management on Growth and Flowering of Cucumber (Cucumis sativus L.) DR Joshiya, JR Vadodaria, BM Nandre, MK Sharma, VR Wankhade Int. J. Curr. Microbiol. App. Sci 9 (2), 133-137 , 2020 2020.0 Citations: 2
A Framework for Finding Outspread News Pattern on Diverse Dataset using Time-Series M Sharma, B Pant, V Singh 2020.0 Citations: 2
Character association studies in grape accessions selected from Leh district of Jammu and Kashmir T Dolkar, MK Sharma, A Kumar Journal of Applied and Natural Science 9 (3), 1782-1786 , 2017 2017.0 Citations: 2
Cellulose utilizing ability of wild and cultivated mushrooms A Doshi, JF Munot, M Sharma 2015.0 Citations: 2
A Hybrid Approach towards Cost Effective Model for Handwritten Character Recognition N Chauhan, M Sharma, P Singh International Journal of Computer Applications 95 (14) , 2014 2014.0 Citations: 2
An Analytical Comparison of Inpainting Techniques for Effective Selection P Singh, M Sharma, N Chauhan International Journal of Computer Applications 95 (14) , 2014 2014.0 Citations: 2
Status of fish diversity and their Habitat Ecology in the upper Ganga Basin, Uttarakhand DS Malik, MK Sharma, K Sharma, AK Sharma Citations: 2
