Dr. MUHAMMAD RUKUNUDDIN GHALIB | Vellore Institute of Technology (original) (raw)

Papers by Dr. MUHAMMAD RUKUNUDDIN GHALIB

Research paper thumbnail of Live video streaming service with pay-as-you-use model on Ethereum Blockchain and InterPlanetary file system

Research paper thumbnail of A novel method for analysis of microarray cancer data using genetic algorithms and constructive neural networks

International journal of applied engineering research, 2014

Research paper thumbnail of A naive-bayes approach for disease diagnosis with analysis of disease type and symptoms

International journal of applied engineering research, 2015

Research paper thumbnail of Detection And Classification Of Human Malignant Melanoma Using Cad Approach

Cancer is one of the dreadful diseases in today’s world. Skin cancer is one among those. Manual m... more Cancer is one of the dreadful diseases in today’s world. Skin cancer is one among those. Manual methods have been available, still a contribution towards computer aided diagnostic in the field of medicine plays a challenging role. The objective of the paper is to detect and classify the skin image and find if it is a melanoma or non melanoma images. This paper includes the method for image enhancement as adaptive median filter, segmentation as a hybrid method and the feature extraction to be a hybrid method and finally the KNN classifier is used to classify the images. The total of 600 images is taken and the efficiency is said to be 96.8%.

Research paper thumbnail of Efficient Shot Boundary Detection with Multiple Visual Representations

Mobile Information Systems, Oct 10, 2022

Due to the unlimited growth of video-capturing devices and media, searching and finding a particu... more Due to the unlimited growth of video-capturing devices and media, searching and finding a particular video in this huge database becomes a laborious as well as expensive task. Information-rich shots are the inevitable factor of the content-based video processing (CBVP) system. Hence, shot boundary detection (SBD) becomes the basic step of all content-based video retrieval processes.)e accuracy of the existing SBD methods highly suffers from false positives and false negatives due to the presence of multiple variants. An efficient SBD method with multiple invariant features is proposed in this paper. A right combination of invariant features such as edge change ratio (ECR), colour layout descriptor (CLD), and scale-invariant feature transform (SIFT) key point descriptors helped to improve the accuracy level of SBD. As the selected features are invariant to most of the variants in video frames, such as illuminance changes, motion, scaling, and rotation, a markable reduction in false detection is possible. Support vector machine (SVM) classifier is used for the classification of frames into transition frames and shot frames.)is proposed method is experimented and analysed with the standard SBD dataset TRECVid 2007 videos.)e experimental results are compared with some state-of-art methods, and our method shows better performance with a 97% of F1 score.

Research paper thumbnail of Federated Machine Learning For Augmenting The Safekeeping of Critical Energy Infrastructures

In the recent years, there have been an increase in attacks targeting Supervisory Control and Dat... more In the recent years, there have been an increase in attacks targeting Supervisory Control and Data Acquisition (SCADA) infrastructures as there are many sensitive data released from peripheral devices. Wind-turbine systems are considered to be the most complex Cyber-Physical infrastructures.A privacy preserving Federated Machine Learning solution is proposed in order detect any possible anomalies in such infrastructures. Instead of centralizing the wind-turbine data into a common server, Federated Machine Learning allows the data to remain on-premise in the infrastructure. This enables the responsible authorities to consider the advantages of Machine Learning, and simultaneously protect their privacy. Different federated machine learning models namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Radial Basis Function (RBF), Multi-Layer Perceptron (MLP) and Random Forest (RF) are deployed to analyze the anomalies in the wind turbines. It is inferred from the experimental r...

Research paper thumbnail of Detection and Classification of Breast Cancer Using Machine Learning Techniques for Ultrasound Images

International Journal of Engineering Trends and Technology

Research paper thumbnail of A novel Rough-Fuzzy based clustering algorithm integrating reformulated fuzziness parameter for microarray gene expression analysis

International journal of applied engineering research, 2014

Research paper thumbnail of A novel method for vehicle detection in high-resolution aerial remote sensing images using YOLT approach

Multimedia Tools and Applications, 2022

Research paper thumbnail of Knowledge-based mining with the game-theoretic rough set approach to handling inconsistent healthcare data

International Journal of High Performance Systems Architecture, 2021

Research paper thumbnail of Prediction of IIoT traffic using a modified whale optimization approach integrated with random forest classifier

The Journal of Supercomputing, 2022

Research paper thumbnail of Sequential Pattern based Activity Recognition model for Ambient Computing

International Journal of Advanced Intelligence Paradigms, 2018

Research paper thumbnail of A pioneering Cryptic Random Projection based approach for privacy preserving data mining

2009 IEEE International Conference on Information Reuse & Integration, 2009

Privacy is the most important apprehension in many data mining applications. In this paper a new ... more Privacy is the most important apprehension in many data mining applications. In this paper a new technique called Cryptic Random Projection, solves the re-identification quandary (which is found in the conventional random projections).Here this encryption based random projection assigns secret keys to the positions of random matrix elements and not to the random numbers. We have addressed two kinds of random sequences for generating the random sequences called determinist and indeterminist random sequences and encrypted it in a new way so that the original data cannot be re-identified. We have also optimized the privacy level which toughens the re-identification of original data without compromising the processing speed and data utility. We hope the projected solution will tarmac way for investigation track and toil well according to the evaluation metrics including hiding effects, data utility, and time performance.

Research paper thumbnail of An Improved Segmentation Technique Based on Delaunay Triangulations for Breast Infiltration/Tumor Detection from

— Breast tumor segmentation and analysis is an important step for doctors in deciding the stage o... more — Breast tumor segmentation and analysis is an important step for doctors in deciding the stage of cancer and to proceed for further treatment. Segmentation of image is a crucial step in image processing which further helps in classification of image based on the features extracted. The segmentation technique in most of the approaches uses similar kind of algorithm for segmentation of region of interest. This paper presents a new approach for preprocessing and segmenting out the infiltration and tumor regions from digital mammograms using two techniques involving iterative and non iterative algorithms of Delaunay triangulation. The preprocessing involves hybrid filter for noise removal and image enhancement. The iterative algorithm for segmentation works to get an idea of shape of infiltration/tumor in the breast. The proposed algorithm uses Voronoi properties to partition an image into regions of similarity followed by Delaunay triangulation. The advantage of this technique is it w...

Research paper thumbnail of Microarray Gene Expression Data Mining using High End Clustering Algorithm based on Attraction-Repulsion Technique

Microarray Gene expression data analysis is one of the key domains in the modern cellular and mol... more Microarray Gene expression data analysis is one of the key domains in the modern cellular and molecular biology system design and analysis; shortly we called it computational simulation of genome-wide expression from DNA hybridization. We present here a high end clustering algorithm basically a technique following the inspiration led by natural attraction and the repulsion processes. It groups the similarly expressed genes in same clusters, co-expressed and differently expressed ones in different clusters. Most importantly, it takes into account of the outliers in an efficient manner by not allowing them to interfere with the similarly expressed gene clusters on the fly. In the first clustering process, it calculates the distances of all the genes in a proximity range set in prior, henceforth attracting all the least distant genes from the seed gene. Varying the proximity range in the subsequent run, repulse the maximally distant genes from the same cluster, thereby achieving a near...

Research paper thumbnail of Development of Platform Independent M-Learning Content

There has been a lot of advancement in mobile technology. The perception of a mobile as mere comm... more There has been a lot of advancement in mobile technology. The perception of a mobile as mere communication device underwent significant changes. One such change is M-learning which has taken its roots from e-learning. Mobile learning (M-learning) provides educational opportunities through mobile phones, PDA, digital media players. The best feature about M-learning is that exact information can be grasped anytime, anywhere without many constraints. Though, M-learning requires researcher's attention in developing issues, processing capabilities and small screen displays. The only major problem with M-learning is the difficulty regarding platform dependency due to different operating systems. The paper discusses about mobile learning technologies, platform independent content and challenges for success of M-learning. It is proved that most of the learners in India have mobile phones and m-learning is an upcoming research field that aims at transition of learning tools from digital ...

Research paper thumbnail of KM-LA: knowledge-based mining for linear analysis of inconsistent medical data for healthcare applications

Personal and Ubiquitous Computing, 2021

Healthcare data analysis is a prominent field of research supporting information technologies in ... more Healthcare data analysis is a prominent field of research supporting information technologies in the medical industry. Handling large volumes of data and mining them for application-related services requires time-efficient and less complex processing. With the implication of machine learning in computing processes, the analysis systems and mining performance are improved. In this manuscript, knowledge-based mining with a linear analysis (KM-LA) model is presented. This analysis model relies on a knowledge base and definitive learning in handling big medical data for health application-centric services. This proposal aims to provide a definite linear solution for medical data mining through less complex analysis for simpler healthcare services. The analysis model is proposed to reduce the inconsistency in handling extensive medical data without causing service failures. The linear analysis model’s performance is verified using suitable experiments to verify service latency, analysis ...

Research paper thumbnail of Microarray Gene Expression Data Analysis Using Enhanced K-Means Clustering Method

This Clustering analysis method is one of the important methods which can influence clustering re... more This Clustering analysis method is one of the important methods which can influence clustering results directly. Among all the clustering methods, k-means clustering is one of the most popular schemes owing to its simplicity and practicality. In this paper we’ve discussed the standard clustering algorithm and analyzed the outcomes of an enhanced k-means algorithm such that it is possible to calculate the distance between all data objects and all cluster centre in each iteration which makes the efficiency of clustering high. This paper basically reviews the method utilized in processing and analysis of gene expression data generated using microarrays. This type of experiment allows determining relative levels of mRNA abundance in a set of tissues or cell populations for thousands of genes simultaneously. We have proposed and implemented an enhanced k-means algorithm which stabilizes and thereby increases the performance in terms of cluster output.

Research paper thumbnail of A hybrid segmentation approach for detection and classification of skin cancer

Biomedical Research-tokyo, 2017

Advancement in Computer Aided Diagnostic system (CAD) enhances the detection and classification o... more Advancement in Computer Aided Diagnostic system (CAD) enhances the detection and classification of domain experts and reduces the time rapidly for them. The CAD systems can be used in hospitals as an alternate method. The objective of the paper is to present the effectiveness of the detection and classification of skin cancer. The proposed methodology concentrates on comparing the median filter and Adaptive Median Filter (AMF) and suggesting on one, the segmentation can be done by a hybrid approach where the marker controlled watershed algorithm is fused with the active contour algorithm, the feature extraction is done with the help of basic statistical methods and the Grey Level Co- Occurrence Matrix (GLCM) with the Support Vector Machine (SVM) for classification. SVM is used to classify the input as cancerous or not. The experiment is carried out on 250 images consists of 100 normal images and 150 abnormal images (benign and melanoma images) from a skin dataset. The classification...

Research paper thumbnail of CoT-Enabled Robust Surveillance System using Fog Machine Learning

Surveillance system is a method of securing resources and loss of lives against fire, gas leakage... more Surveillance system is a method of securing resources and loss of lives against fire, gas leakage, intruder, earthquake, and weather. In today’s time, people own home, farm, factory, office etc. It has become more crucial to monitor everything for securing resources and loss of lives against fire, gas leakage, intruder, earthquake. As a part of surveillance, monitoring weather is also essential. Climate change and agriculture are interrelated processes, Today's sophisticated commercial farming like weather monitoring, suffers from a lack of precision, which results huge loss in farm. Monitoring residential and commercial arenas throughout is an efficient technique to decrease personal and property losses due to fire, gas leakage, earthquake catastrophes. Internet of Things make it possible and can be implemented separately for each thing or site. But it is very difficult to monitor each site and have centralized access of it across the world. This arises the need of heterogenous...

Research paper thumbnail of Live video streaming service with pay-as-you-use model on Ethereum Blockchain and InterPlanetary file system

Research paper thumbnail of A novel method for analysis of microarray cancer data using genetic algorithms and constructive neural networks

International journal of applied engineering research, 2014

Research paper thumbnail of A naive-bayes approach for disease diagnosis with analysis of disease type and symptoms

International journal of applied engineering research, 2015

Research paper thumbnail of Detection And Classification Of Human Malignant Melanoma Using Cad Approach

Cancer is one of the dreadful diseases in today’s world. Skin cancer is one among those. Manual m... more Cancer is one of the dreadful diseases in today’s world. Skin cancer is one among those. Manual methods have been available, still a contribution towards computer aided diagnostic in the field of medicine plays a challenging role. The objective of the paper is to detect and classify the skin image and find if it is a melanoma or non melanoma images. This paper includes the method for image enhancement as adaptive median filter, segmentation as a hybrid method and the feature extraction to be a hybrid method and finally the KNN classifier is used to classify the images. The total of 600 images is taken and the efficiency is said to be 96.8%.

Research paper thumbnail of Efficient Shot Boundary Detection with Multiple Visual Representations

Mobile Information Systems, Oct 10, 2022

Due to the unlimited growth of video-capturing devices and media, searching and finding a particu... more Due to the unlimited growth of video-capturing devices and media, searching and finding a particular video in this huge database becomes a laborious as well as expensive task. Information-rich shots are the inevitable factor of the content-based video processing (CBVP) system. Hence, shot boundary detection (SBD) becomes the basic step of all content-based video retrieval processes.)e accuracy of the existing SBD methods highly suffers from false positives and false negatives due to the presence of multiple variants. An efficient SBD method with multiple invariant features is proposed in this paper. A right combination of invariant features such as edge change ratio (ECR), colour layout descriptor (CLD), and scale-invariant feature transform (SIFT) key point descriptors helped to improve the accuracy level of SBD. As the selected features are invariant to most of the variants in video frames, such as illuminance changes, motion, scaling, and rotation, a markable reduction in false detection is possible. Support vector machine (SVM) classifier is used for the classification of frames into transition frames and shot frames.)is proposed method is experimented and analysed with the standard SBD dataset TRECVid 2007 videos.)e experimental results are compared with some state-of-art methods, and our method shows better performance with a 97% of F1 score.

Research paper thumbnail of Federated Machine Learning For Augmenting The Safekeeping of Critical Energy Infrastructures

In the recent years, there have been an increase in attacks targeting Supervisory Control and Dat... more In the recent years, there have been an increase in attacks targeting Supervisory Control and Data Acquisition (SCADA) infrastructures as there are many sensitive data released from peripheral devices. Wind-turbine systems are considered to be the most complex Cyber-Physical infrastructures.A privacy preserving Federated Machine Learning solution is proposed in order detect any possible anomalies in such infrastructures. Instead of centralizing the wind-turbine data into a common server, Federated Machine Learning allows the data to remain on-premise in the infrastructure. This enables the responsible authorities to consider the advantages of Machine Learning, and simultaneously protect their privacy. Different federated machine learning models namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Radial Basis Function (RBF), Multi-Layer Perceptron (MLP) and Random Forest (RF) are deployed to analyze the anomalies in the wind turbines. It is inferred from the experimental r...

Research paper thumbnail of Detection and Classification of Breast Cancer Using Machine Learning Techniques for Ultrasound Images

International Journal of Engineering Trends and Technology

Research paper thumbnail of A novel Rough-Fuzzy based clustering algorithm integrating reformulated fuzziness parameter for microarray gene expression analysis

International journal of applied engineering research, 2014

Research paper thumbnail of A novel method for vehicle detection in high-resolution aerial remote sensing images using YOLT approach

Multimedia Tools and Applications, 2022

Research paper thumbnail of Knowledge-based mining with the game-theoretic rough set approach to handling inconsistent healthcare data

International Journal of High Performance Systems Architecture, 2021

Research paper thumbnail of Prediction of IIoT traffic using a modified whale optimization approach integrated with random forest classifier

The Journal of Supercomputing, 2022

Research paper thumbnail of Sequential Pattern based Activity Recognition model for Ambient Computing

International Journal of Advanced Intelligence Paradigms, 2018

Research paper thumbnail of A pioneering Cryptic Random Projection based approach for privacy preserving data mining

2009 IEEE International Conference on Information Reuse & Integration, 2009

Privacy is the most important apprehension in many data mining applications. In this paper a new ... more Privacy is the most important apprehension in many data mining applications. In this paper a new technique called Cryptic Random Projection, solves the re-identification quandary (which is found in the conventional random projections).Here this encryption based random projection assigns secret keys to the positions of random matrix elements and not to the random numbers. We have addressed two kinds of random sequences for generating the random sequences called determinist and indeterminist random sequences and encrypted it in a new way so that the original data cannot be re-identified. We have also optimized the privacy level which toughens the re-identification of original data without compromising the processing speed and data utility. We hope the projected solution will tarmac way for investigation track and toil well according to the evaluation metrics including hiding effects, data utility, and time performance.

Research paper thumbnail of An Improved Segmentation Technique Based on Delaunay Triangulations for Breast Infiltration/Tumor Detection from

— Breast tumor segmentation and analysis is an important step for doctors in deciding the stage o... more — Breast tumor segmentation and analysis is an important step for doctors in deciding the stage of cancer and to proceed for further treatment. Segmentation of image is a crucial step in image processing which further helps in classification of image based on the features extracted. The segmentation technique in most of the approaches uses similar kind of algorithm for segmentation of region of interest. This paper presents a new approach for preprocessing and segmenting out the infiltration and tumor regions from digital mammograms using two techniques involving iterative and non iterative algorithms of Delaunay triangulation. The preprocessing involves hybrid filter for noise removal and image enhancement. The iterative algorithm for segmentation works to get an idea of shape of infiltration/tumor in the breast. The proposed algorithm uses Voronoi properties to partition an image into regions of similarity followed by Delaunay triangulation. The advantage of this technique is it w...

Research paper thumbnail of Microarray Gene Expression Data Mining using High End Clustering Algorithm based on Attraction-Repulsion Technique

Microarray Gene expression data analysis is one of the key domains in the modern cellular and mol... more Microarray Gene expression data analysis is one of the key domains in the modern cellular and molecular biology system design and analysis; shortly we called it computational simulation of genome-wide expression from DNA hybridization. We present here a high end clustering algorithm basically a technique following the inspiration led by natural attraction and the repulsion processes. It groups the similarly expressed genes in same clusters, co-expressed and differently expressed ones in different clusters. Most importantly, it takes into account of the outliers in an efficient manner by not allowing them to interfere with the similarly expressed gene clusters on the fly. In the first clustering process, it calculates the distances of all the genes in a proximity range set in prior, henceforth attracting all the least distant genes from the seed gene. Varying the proximity range in the subsequent run, repulse the maximally distant genes from the same cluster, thereby achieving a near...

Research paper thumbnail of Development of Platform Independent M-Learning Content

There has been a lot of advancement in mobile technology. The perception of a mobile as mere comm... more There has been a lot of advancement in mobile technology. The perception of a mobile as mere communication device underwent significant changes. One such change is M-learning which has taken its roots from e-learning. Mobile learning (M-learning) provides educational opportunities through mobile phones, PDA, digital media players. The best feature about M-learning is that exact information can be grasped anytime, anywhere without many constraints. Though, M-learning requires researcher's attention in developing issues, processing capabilities and small screen displays. The only major problem with M-learning is the difficulty regarding platform dependency due to different operating systems. The paper discusses about mobile learning technologies, platform independent content and challenges for success of M-learning. It is proved that most of the learners in India have mobile phones and m-learning is an upcoming research field that aims at transition of learning tools from digital ...

Research paper thumbnail of KM-LA: knowledge-based mining for linear analysis of inconsistent medical data for healthcare applications

Personal and Ubiquitous Computing, 2021

Healthcare data analysis is a prominent field of research supporting information technologies in ... more Healthcare data analysis is a prominent field of research supporting information technologies in the medical industry. Handling large volumes of data and mining them for application-related services requires time-efficient and less complex processing. With the implication of machine learning in computing processes, the analysis systems and mining performance are improved. In this manuscript, knowledge-based mining with a linear analysis (KM-LA) model is presented. This analysis model relies on a knowledge base and definitive learning in handling big medical data for health application-centric services. This proposal aims to provide a definite linear solution for medical data mining through less complex analysis for simpler healthcare services. The analysis model is proposed to reduce the inconsistency in handling extensive medical data without causing service failures. The linear analysis model’s performance is verified using suitable experiments to verify service latency, analysis ...

Research paper thumbnail of Microarray Gene Expression Data Analysis Using Enhanced K-Means Clustering Method

This Clustering analysis method is one of the important methods which can influence clustering re... more This Clustering analysis method is one of the important methods which can influence clustering results directly. Among all the clustering methods, k-means clustering is one of the most popular schemes owing to its simplicity and practicality. In this paper we’ve discussed the standard clustering algorithm and analyzed the outcomes of an enhanced k-means algorithm such that it is possible to calculate the distance between all data objects and all cluster centre in each iteration which makes the efficiency of clustering high. This paper basically reviews the method utilized in processing and analysis of gene expression data generated using microarrays. This type of experiment allows determining relative levels of mRNA abundance in a set of tissues or cell populations for thousands of genes simultaneously. We have proposed and implemented an enhanced k-means algorithm which stabilizes and thereby increases the performance in terms of cluster output.

Research paper thumbnail of A hybrid segmentation approach for detection and classification of skin cancer

Biomedical Research-tokyo, 2017

Advancement in Computer Aided Diagnostic system (CAD) enhances the detection and classification o... more Advancement in Computer Aided Diagnostic system (CAD) enhances the detection and classification of domain experts and reduces the time rapidly for them. The CAD systems can be used in hospitals as an alternate method. The objective of the paper is to present the effectiveness of the detection and classification of skin cancer. The proposed methodology concentrates on comparing the median filter and Adaptive Median Filter (AMF) and suggesting on one, the segmentation can be done by a hybrid approach where the marker controlled watershed algorithm is fused with the active contour algorithm, the feature extraction is done with the help of basic statistical methods and the Grey Level Co- Occurrence Matrix (GLCM) with the Support Vector Machine (SVM) for classification. SVM is used to classify the input as cancerous or not. The experiment is carried out on 250 images consists of 100 normal images and 150 abnormal images (benign and melanoma images) from a skin dataset. The classification...

Research paper thumbnail of CoT-Enabled Robust Surveillance System using Fog Machine Learning

Surveillance system is a method of securing resources and loss of lives against fire, gas leakage... more Surveillance system is a method of securing resources and loss of lives against fire, gas leakage, intruder, earthquake, and weather. In today’s time, people own home, farm, factory, office etc. It has become more crucial to monitor everything for securing resources and loss of lives against fire, gas leakage, intruder, earthquake. As a part of surveillance, monitoring weather is also essential. Climate change and agriculture are interrelated processes, Today's sophisticated commercial farming like weather monitoring, suffers from a lack of precision, which results huge loss in farm. Monitoring residential and commercial arenas throughout is an efficient technique to decrease personal and property losses due to fire, gas leakage, earthquake catastrophes. Internet of Things make it possible and can be implemented separately for each thing or site. But it is very difficult to monitor each site and have centralized access of it across the world. This arises the need of heterogenous...