Dr. Pankaj Dadheech | Swami Kesvanand Institute Of Technology (original) (raw)

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Papers by Dr. Pankaj Dadheech

Research paper thumbnail of Chebyshev polynomial approximation in CNN for zero-knowledge encrypted data analysis

Journal of Discrete Mathematical Sciences & Cryptography/Journal of discrete mathematical sciences & cryptography, 2024

Research paper thumbnail of Merkle-Damgård hash functions and blockchains : Securing electronic health records

Journal of Discrete Mathematical Sciences & Cryptography/Journal of discrete mathematical sciences & cryptography, 2024

Research paper thumbnail of Modular metric spaces : Some fixed-point theorems and application of secure dynamic routing for WSN

Journal of Interdisciplinary Mathematics/Journal of interdisciplinary mathematics, 2024

Research paper thumbnail of Advancing viscoelastic material modeling : Tackling time-dependent behavior with fractional calculus

Journal of Interdisciplinary Mathematics/Journal of interdisciplinary mathematics, 2024

Research paper thumbnail of Enhanced Route navigation control system for turtlebot using human-assisted mobility and 3-D SLAM optimization

Research paper thumbnail of Real-World Implementation of Cloud Computing New Technologies

Advances in computer and electrical engineering book series, Mar 22, 2024

Research paper thumbnail of An Efficient Hybrid Approach for Intrusion Detection in Cyber Traffic Using Autoencoders

Research paper thumbnail of Secret Data Transmission Using Advanced Morphological Component Analysis and Steganography

Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions

Research paper thumbnail of A Highly Sensitive LC–MS/MS Method Development and Validation of Fedratinib in Human Plasma and Pharmacokinetic Evaluation in Healthy Rabbits

Current Pharmaceutical Analysis, 2020

Background: A simple and sensitive quantitation analytical technique by liquid chromatography–tan... more Background: A simple and sensitive quantitation analytical technique by liquid chromatography–tandem mass spectrometry (LC-MS/MS) is essential for fedratinib in biological media with kinetic study in healthy rabbits. Objective: The main objectives of the present research work are to LC-MS/MS method development and validate procedure for the quantitation of fedratinib and its application to kinetic study in rabbits. Methods: Separation of processed samples were employed on zorbax SB C18 column (50mm×4.6 mm) 3.5µm with a movable phase of methanol, acetonitrile and 0.1% formic acid in the ratio of 30:60:10. The movable phase was monitored through column at 0.8 ml/min flow rate. The drug and ibrutinib internal standard (IS) were evaluated by monitoring the transitions of m/z -525.260/57.07 and 441.2/55.01 for fedratinib and IS respectively in multiple reaction monitoring mode. Results: The linear equation and coefficient of correlation (R2) results were y =0.00348x+0.00245 and 0.9984, r...

Research paper thumbnail of Classification and Localization of COVID-19 based on a Pneumonia Radiograph using a Deep Learning Approach

Research paper thumbnail of Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks

Intelligent Automation and Soft Computing, 2022

Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can... more Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required during DA remained unsolved. The detection of objects belonging to the same event into specific regions by the Bayes Node is distributed through the Sensor Nodes (SNs). Multi-Sensor Data Synchronization Scheduling (MSDSS) framework is proposed for efficient DA at the sink in a heterogeneous sensor network. Secure and Energy-Efficient based In-Network Aggregation Sensor Data Routing (SEE-INASDR) is developed based on the Dynamic Routing (DR) structure with reliable data transmission in WSNs. Theoretical analysis and experimental results showed that in WSN, the proposed Bayes Node Energy Polynomial Distribution (BNEPD) technique reduced Energy Drain Rate (EDR) by 39% and reduced 33% of Communication Overhead (CO) using poly distribution algorithm. Similarly, the proposed MSDSS framework increased the Network Lifetime (NL) by 15%. This framework also increased 10.5% of Data Aggregation Routing (DAR). Finally, the SEE-INASDR framework significantly reduced EC by 51% using a Secure and Energy-Efficient Routing Protocol (SEERP).

Research paper thumbnail of Impact Analysis to Detect and Mitigate Distributed Denial of Service Attacks with Ryu-SDN Controller: A Comparative Analysis of Four Different Machine Learning Classification Algorithms

SN computer science, Jun 17, 2023

Research paper thumbnail of Predicting Agriculture Yields Based on Machine Learning using Regression and Deep Learning

IEEE Access

Agriculture contributes a significant amount to the economy of India due to the dependence on hum... more Agriculture contributes a significant amount to the economy of India due to the dependence on human beings for their survival. The main obstacle to food security is population expansion leading to rising demand for food. Farmers must produce more on the same land to boost the supply. Through crop yield prediction, technology can assist farmers in producing more. This paper's primary goal is to predict crop yield utilizing the variables of rainfall, crop, meteorological conditions, area, production, and yield that have posed a serious threat to the long-term viability of agriculture. Crop yield prediction is a decisionsupport tool that uses machine learning and deep learning that can be used to make decisions about which crops to produce and what to do in the crop's growing season. It can decide which crops to produce and what to do in the crop's growing season. Regardless of the distracting environment, machine learning and deep learning algorithms are utilized in crop selection to reduce agricultural yield output losses. To estimate the agricultural yield, machine learning techniques: decision tree, random forest, and XGBoost regression; deep learning techniques-convolutional neural network and long-short term memory network have been used. Accuracy, root mean square error, mean square error, mean absolute error, standard deviation, and losses are compared. Other machine learning and deep learning methods fall short compared to the random forest and convolutional neural network. The random forest has a maximum accuracy of 98.96%, mean absolute error of 1.97, root mean square error of 2.45, and standard deviation of 1.23. The convolutional neural network has been evaluated with a minimum loss of 0.00060. Consequently, a model is developed that, compared to other algorithms, predicts the yield quite well. The findings are then analyzed using the root mean square error metric to understand better how the model's errors compare to those of the other methods.

Research paper thumbnail of Metaverse

Advances in marketing, customer relationship management, and e-services book series, May 26, 2023

Research paper thumbnail of An optimization of bitmap index compression technique in bulk data movement infrastructure

Bitmap index is most commonly used technique for efficient query processing and mostly in the Dat... more Bitmap index is most commonly used technique for efficient query processing and mostly in the Data warehouse environment. The purpose behind this study to release the occupied disk space after deletion of records. We review the existing technologies of Compression and introduce the bitmap index compression through data pump. According to conventional wisdom bitmap index is more efficient for minimum unique value. But through data pump it doesn't require either bitmap index is created on high degree of cardinality or low degree of cardinality. In this paper, we propose data pump utility for release the disk space in database after deletion of records. Bitmap index point the old location even after deletion of records from table, this utility doesn't release disk space. We have implemented data pump for compression, to release the space and change the index pointing location. Data pump which is often used for logical backups in oracle database. Finally we review the bitmap index which commonly used for industrial purpose and discuss open issues for future evolution and development Subject Classification: 54H30 Applications of general topology to computer science.

Research paper thumbnail of Improved Classification Techniques for the Diagnosis and Prognosis of Cancer

CRC Press eBooks, Mar 19, 2021

Research paper thumbnail of A hybrid cluster technique for improving the efficiency of colour image segmentation

World Review of Entrepreneurship, Management and Sustainable Development, 2020

Research paper thumbnail of A WSN-Based Insect Monitoring and Pest Control System Through Behavior Analysis Using Artificial Neural Network

International Journal of Social Ecology and Sustainable Development, Oct 29, 2021

Insect Monitoring includes collecting information about insect activity with the help of using tr... more Insect Monitoring includes collecting information about insect activity with the help of using traps and lures. Many different types of traps are used and they can be divided into the following types - Light traps, Sticky Traps and Pheromone Traps. After trapping the insect, the next step involves monitoring tools to monitor the further behavior of insects. Monitoring includes checking of crop fields for early detection of pests and identification of pests. Identification helps in finding which are the best naturally occurring control agents and assessing the efficiency of pest control actions that already have been taken. The main purpose of this paper is to design the insect monitoring system is to assess insect activity and gain population estimates so we can deploy a solution that will be most effective at protecting our crops. This system involves the use of traps and lures to get information on insect activity. Traps are strategically placed throughout the crop and include natural semi-chemical attractants to draw insects into the traps.

Research paper thumbnail of An enhanced whale optimization algorithm for clustering

Multimedia Tools and Applications, Jul 27, 2022

Research paper thumbnail of A Neural Network-Based Approach for Pest Detection and Control in Modern Agriculture Using Internet of Things

IGI Global eBooks, 2021

The networks acquire an altered move towards the difficulty solving skills rather than that of co... more The networks acquire an altered move towards the difficulty solving skills rather than that of conventional computers. Artificial neural networks are comparatively crude electronic designs based on the neural structure of the brain. The chapter describes two different types of approaches to training, supervised and unsupervised, as well as the real-time applications of artificial neural networks. Based on the character of the application and the power of the internal data patterns we can normally foresee a network to train quite well. ANNs offers an analytical solution to conventional techniques that are often restricted by severe presumptions of normality, linearity, variable independence, etc. The chapter describes the necessities of items required for pest management through pheromones such as different types of pest are explained and also focused on use of pest control pheromones.

Research paper thumbnail of Chebyshev polynomial approximation in CNN for zero-knowledge encrypted data analysis

Journal of Discrete Mathematical Sciences & Cryptography/Journal of discrete mathematical sciences & cryptography, 2024

Research paper thumbnail of Merkle-Damgård hash functions and blockchains : Securing electronic health records

Journal of Discrete Mathematical Sciences & Cryptography/Journal of discrete mathematical sciences & cryptography, 2024

Research paper thumbnail of Modular metric spaces : Some fixed-point theorems and application of secure dynamic routing for WSN

Journal of Interdisciplinary Mathematics/Journal of interdisciplinary mathematics, 2024

Research paper thumbnail of Advancing viscoelastic material modeling : Tackling time-dependent behavior with fractional calculus

Journal of Interdisciplinary Mathematics/Journal of interdisciplinary mathematics, 2024

Research paper thumbnail of Enhanced Route navigation control system for turtlebot using human-assisted mobility and 3-D SLAM optimization

Research paper thumbnail of Real-World Implementation of Cloud Computing New Technologies

Advances in computer and electrical engineering book series, Mar 22, 2024

Research paper thumbnail of An Efficient Hybrid Approach for Intrusion Detection in Cyber Traffic Using Autoencoders

Research paper thumbnail of Secret Data Transmission Using Advanced Morphological Component Analysis and Steganography

Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions

Research paper thumbnail of A Highly Sensitive LC–MS/MS Method Development and Validation of Fedratinib in Human Plasma and Pharmacokinetic Evaluation in Healthy Rabbits

Current Pharmaceutical Analysis, 2020

Background: A simple and sensitive quantitation analytical technique by liquid chromatography–tan... more Background: A simple and sensitive quantitation analytical technique by liquid chromatography–tandem mass spectrometry (LC-MS/MS) is essential for fedratinib in biological media with kinetic study in healthy rabbits. Objective: The main objectives of the present research work are to LC-MS/MS method development and validate procedure for the quantitation of fedratinib and its application to kinetic study in rabbits. Methods: Separation of processed samples were employed on zorbax SB C18 column (50mm×4.6 mm) 3.5µm with a movable phase of methanol, acetonitrile and 0.1% formic acid in the ratio of 30:60:10. The movable phase was monitored through column at 0.8 ml/min flow rate. The drug and ibrutinib internal standard (IS) were evaluated by monitoring the transitions of m/z -525.260/57.07 and 441.2/55.01 for fedratinib and IS respectively in multiple reaction monitoring mode. Results: The linear equation and coefficient of correlation (R2) results were y =0.00348x+0.00245 and 0.9984, r...

Research paper thumbnail of Classification and Localization of COVID-19 based on a Pneumonia Radiograph using a Deep Learning Approach

Research paper thumbnail of Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks

Intelligent Automation and Soft Computing, 2022

Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can... more Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required during DA remained unsolved. The detection of objects belonging to the same event into specific regions by the Bayes Node is distributed through the Sensor Nodes (SNs). Multi-Sensor Data Synchronization Scheduling (MSDSS) framework is proposed for efficient DA at the sink in a heterogeneous sensor network. Secure and Energy-Efficient based In-Network Aggregation Sensor Data Routing (SEE-INASDR) is developed based on the Dynamic Routing (DR) structure with reliable data transmission in WSNs. Theoretical analysis and experimental results showed that in WSN, the proposed Bayes Node Energy Polynomial Distribution (BNEPD) technique reduced Energy Drain Rate (EDR) by 39% and reduced 33% of Communication Overhead (CO) using poly distribution algorithm. Similarly, the proposed MSDSS framework increased the Network Lifetime (NL) by 15%. This framework also increased 10.5% of Data Aggregation Routing (DAR). Finally, the SEE-INASDR framework significantly reduced EC by 51% using a Secure and Energy-Efficient Routing Protocol (SEERP).

Research paper thumbnail of Impact Analysis to Detect and Mitigate Distributed Denial of Service Attacks with Ryu-SDN Controller: A Comparative Analysis of Four Different Machine Learning Classification Algorithms

SN computer science, Jun 17, 2023

Research paper thumbnail of Predicting Agriculture Yields Based on Machine Learning using Regression and Deep Learning

IEEE Access

Agriculture contributes a significant amount to the economy of India due to the dependence on hum... more Agriculture contributes a significant amount to the economy of India due to the dependence on human beings for their survival. The main obstacle to food security is population expansion leading to rising demand for food. Farmers must produce more on the same land to boost the supply. Through crop yield prediction, technology can assist farmers in producing more. This paper's primary goal is to predict crop yield utilizing the variables of rainfall, crop, meteorological conditions, area, production, and yield that have posed a serious threat to the long-term viability of agriculture. Crop yield prediction is a decisionsupport tool that uses machine learning and deep learning that can be used to make decisions about which crops to produce and what to do in the crop's growing season. It can decide which crops to produce and what to do in the crop's growing season. Regardless of the distracting environment, machine learning and deep learning algorithms are utilized in crop selection to reduce agricultural yield output losses. To estimate the agricultural yield, machine learning techniques: decision tree, random forest, and XGBoost regression; deep learning techniques-convolutional neural network and long-short term memory network have been used. Accuracy, root mean square error, mean square error, mean absolute error, standard deviation, and losses are compared. Other machine learning and deep learning methods fall short compared to the random forest and convolutional neural network. The random forest has a maximum accuracy of 98.96%, mean absolute error of 1.97, root mean square error of 2.45, and standard deviation of 1.23. The convolutional neural network has been evaluated with a minimum loss of 0.00060. Consequently, a model is developed that, compared to other algorithms, predicts the yield quite well. The findings are then analyzed using the root mean square error metric to understand better how the model's errors compare to those of the other methods.

Research paper thumbnail of Metaverse

Advances in marketing, customer relationship management, and e-services book series, May 26, 2023

Research paper thumbnail of An optimization of bitmap index compression technique in bulk data movement infrastructure

Bitmap index is most commonly used technique for efficient query processing and mostly in the Dat... more Bitmap index is most commonly used technique for efficient query processing and mostly in the Data warehouse environment. The purpose behind this study to release the occupied disk space after deletion of records. We review the existing technologies of Compression and introduce the bitmap index compression through data pump. According to conventional wisdom bitmap index is more efficient for minimum unique value. But through data pump it doesn't require either bitmap index is created on high degree of cardinality or low degree of cardinality. In this paper, we propose data pump utility for release the disk space in database after deletion of records. Bitmap index point the old location even after deletion of records from table, this utility doesn't release disk space. We have implemented data pump for compression, to release the space and change the index pointing location. Data pump which is often used for logical backups in oracle database. Finally we review the bitmap index which commonly used for industrial purpose and discuss open issues for future evolution and development Subject Classification: 54H30 Applications of general topology to computer science.

Research paper thumbnail of Improved Classification Techniques for the Diagnosis and Prognosis of Cancer

CRC Press eBooks, Mar 19, 2021

Research paper thumbnail of A hybrid cluster technique for improving the efficiency of colour image segmentation

World Review of Entrepreneurship, Management and Sustainable Development, 2020

Research paper thumbnail of A WSN-Based Insect Monitoring and Pest Control System Through Behavior Analysis Using Artificial Neural Network

International Journal of Social Ecology and Sustainable Development, Oct 29, 2021

Insect Monitoring includes collecting information about insect activity with the help of using tr... more Insect Monitoring includes collecting information about insect activity with the help of using traps and lures. Many different types of traps are used and they can be divided into the following types - Light traps, Sticky Traps and Pheromone Traps. After trapping the insect, the next step involves monitoring tools to monitor the further behavior of insects. Monitoring includes checking of crop fields for early detection of pests and identification of pests. Identification helps in finding which are the best naturally occurring control agents and assessing the efficiency of pest control actions that already have been taken. The main purpose of this paper is to design the insect monitoring system is to assess insect activity and gain population estimates so we can deploy a solution that will be most effective at protecting our crops. This system involves the use of traps and lures to get information on insect activity. Traps are strategically placed throughout the crop and include natural semi-chemical attractants to draw insects into the traps.

Research paper thumbnail of An enhanced whale optimization algorithm for clustering

Multimedia Tools and Applications, Jul 27, 2022

Research paper thumbnail of A Neural Network-Based Approach for Pest Detection and Control in Modern Agriculture Using Internet of Things

IGI Global eBooks, 2021

The networks acquire an altered move towards the difficulty solving skills rather than that of co... more The networks acquire an altered move towards the difficulty solving skills rather than that of conventional computers. Artificial neural networks are comparatively crude electronic designs based on the neural structure of the brain. The chapter describes two different types of approaches to training, supervised and unsupervised, as well as the real-time applications of artificial neural networks. Based on the character of the application and the power of the internal data patterns we can normally foresee a network to train quite well. ANNs offers an analytical solution to conventional techniques that are often restricted by severe presumptions of normality, linearity, variable independence, etc. The chapter describes the necessities of items required for pest management through pheromones such as different types of pest are explained and also focused on use of pest control pheromones.