Breast cancer is the most prevalent form of cancer that can strike at any age; the higher the age... more Breast cancer is the most prevalent form of cancer that can strike at any age; the higher the age, the greater the risk. The presence of malignant tissue has become more frequent in women. Although medical therapy has improved breast cancer diagnostic and treatment methods, still the death rate remains high due to failure of diagnosing breast cancer in its early stages. A classification approach for mammography images based on nonsubsampled contourlet transform (NSCT) is proposed in order to investigate it. The proposed method uses multiresolution NSCT decomposition to the region of interest (ROI) of mammography images and then uses Z-moments for extracting features from the NSCT-decomposed images. The matrix is formed by the components that are extracted from the region of interest and are then subjected to singular value decomposition (SVD) in order to remove the essential features that can generalize globally. The method employs a support vector machine (SVM) classification algor...
International Journal of Environmental Science and Technology
The change in habits and lifestyle of citizens during health crisis like COVID-19 pandemic has re... more The change in habits and lifestyle of citizens during health crisis like COVID-19 pandemic has resulted in an unprecedented increase in the struggles for solid waste management across the globe. Not only underdeveloped and developing economies are struggling with the challenges posed by mounting piles of infectious waste but even developed countries are adversely affected in similar manner. The routine waste management strategies followed by various countries are overturned due extremely altered trends in the amount and type of waste generated by households and medical facilities. The aim of this paper is to study and list the best available waste management policies adopted by some developing, developed and underdeveloped economies. The listed case studies were selected due to some unique steps undertaken for solid waste disposal during pandemic. The findings revealed that the guidelines issued by WHO for waste management of corona virus infected waste were followed by these nations and certain additional preventive steps were taken. Due to unavailability of single framework as prescribed by international authorities, various sustainable steps taken by individual countries to curb the pandemic menace can be useful in the present context. Few of these measures can be permanently adopted at global level by other nations for handling the pandemic like situations efficiently in pandemic situations.
Computational and Mathematical Methods in Medicine, Apr 14, 2022
Critical ML or CML is a critical approach development of the standard ML (SML) procedure. Convent... more Critical ML or CML is a critical approach development of the standard ML (SML) procedure. Conventional ML (ML) is being used in radiology departments where complex neuroimages are discriminated using ML technology. Radiologists and researchers found that sole decision by the ML algorithms is not accurate enough to implement the treatment procedure. Thus, an intelligent decision is required further by the radiologists after evaluating the ML outcomes. The current research is based on the critical ML, where radiologists' critical thinking ability, IQ (intelligence quotient), and experience in radiology have been examined to understand how these factors affect the accuracy of neuroimaging discrimination. A primary quantitative survey has been carried out, and the data were analysed in IBM SPSS. The results showed that experience in works has a positive impact on neuroimaging discrimination accuracy. IQ and trained ML are also responsible for improving the accuracy as well. Thus, radiologists with more experience in that field are able to improve the discriminative and diagnostic capability of CML.
Resource management efficiency can be a beneficial step toward optimizing power consumption in so... more Resource management efficiency can be a beneficial step toward optimizing power consumption in software-hardware integrated systems. Languages such as C, C++, and Fortran have been extremely popular for dealing with optimization, memory management, and other resource management. We investigate novel algorithmic architectures capable of optimizing resource requirements and increasing energy efficiency. The experimental results obtained with C++ can be extended to other programming languages as well. We emphasize the inherent drawbacks of memory management operators. These operators are intended to be extremely generic in their application, just as the concept of dynamic memory is. As a result, they are unable to take advantage of the various optimization techniques and opportunities that specific use cases present. Each source code file is modeled after its own distinct memory usage pattern, which can be used to speed up memory management routines. Such concepts are frequently time-c...
Pandemics and epidemics have plagued humanity throughout history. The modern world faced one such... more Pandemics and epidemics have plagued humanity throughout history. The modern world faced one such devastating disease in 2019 called Coronavirus. As the world is still trying to recover from Coronavirus, an epidemic that might not see its end anytime soon. This study focuses on analyzing and predicting the future hospital admissions that arise due to Covid-19 .For this study, the choice of country is the United Kingdom. The data has been procured from reliable internet sources to carry out all necessary experiments. The data set contains daily hospitalisations due to Covid-19 in the United Kingdom. To carry out the time-series forecasting, the predictive model is built using a special Recurrent Neural Network, also known as Long Short-Term Memory (LSTM) . The final model was built using a Stacked LSTM to predict the number of hospitalisations due to Covid-19 that may arise in the United Kingdom for the next twenty days from the last day of the dataset used. The results of this stud...
This study proposes a novel glaucoma identification system from fundus images through the deep be... more This study proposes a novel glaucoma identification system from fundus images through the deep belief network (DBN) optimized by the elephant-herding optimization (EHO) algorithm. Initially, the input image undergoes the preprocessing steps of noise removal and enhancement processes, followed by optical disc (OD) and optical cup (OC) segmentation and extraction of structural, intensity, and textural features. Most discriminative features are then selected using the ReliefF algorithm and passed to the DBN for classification into glaucomatous or normal. To enhance the classification rate of the DBN, the DBN parameters are fine-tuned by the EHO algorithm. The model has experimented on public and private datasets with 7280 images, which attained a maximum classification rate of 99.4%, 100% specificity, and 99.89% sensitivity. The 10-fold cross validation reduced the misclassification and attained 98.5% accuracy. Investigations proved the efficacy of the proposed method in avoiding bias,...
In the modern world, due to the usage of high-power chemical-based cosmetics, climate change, and... more In the modern world, due to the usage of high-power chemical-based cosmetics, climate change, and other major factors, skin cancer has been increasing among individuals. Skin cancer is considered as the most common malignant disorder, and there are more than a million cases being recorded with this disease every year. Extensive studies have already been performed to identify the risk factors and causative agents for skin cancer, including lifestyle changes and eatery patterns among individuals. The most common type of skin cancer is classified into basal cell carcinoma and squamous cell carcinoma. The researcher intends to conduct the research with the primary goal of determining the important factors in blockchain technology in the treatment of skin cancer in senior people. The application of new technologies such as blockchain has enabled offering better promises to health care professionals in addressing skin cancer in a more effective manner. These tools supported in evaluating ...
Phishing is the most prominent cyber-crime that uses camouflaged e-mail as a weapon. In simple wo... more Phishing is the most prominent cyber-crime that uses camouflaged e-mail as a weapon. In simple words, it is defined as the strategy adopted by fraudsters in-order-to get private details from persons by professing to be from wellknown channels like offices, bank, or a government organization. In this era of modernization, electronic mails are accustomed globally as communiqué channel for both private and professional purposes. The particulars exchanged over emails are often confidential and sensitive for example info of bank statements, payment bills, debit-credit reports, and authentication data. This makes e-mails precious for hackers because they can exploit these details for maleficent intends. The main goal of the attackers is to acquire personal details by deceiving the e-mail recipient to click noxious link or download the attachment under false pretences. In the last few years, there is an exponential rise in cyber threats including the major ones, phishing e-mails have result in huge monetary and identity losses. Several models have been developed to separate ham and phished e-mails but attackers are always trying new methods to invade the privacy of the people. Hence, there is dire need to perpetually develop new models or to upgrade the existing ones. The focus of the paper is to elaborate that specifically centers around on both machinelearning (ML) and deep-learning (DL) approaches for detecting phishing e-mails. It shows comparative analysis and assessment of various DL and ML models that were proposed in the last few decades to classify phishing e-mails at different stages of crime in a systematic manner. This paper discusses the problem's concept, its explication, and the anticipated future directions.
International Journal of Current Science Research and Review
Blockchain has been found of great use in various sectors and this technology promises much more ... more Blockchain has been found of great use in various sectors and this technology promises much more because of the high level of security it provides and blockchain provides us trade without the need of any mediators so Land holding system seems to be a very promising area of interest. All the countries around the world are now implementing blockchain in the area of land registrations in India, we should also consider it as a viable option. The blockchain has provided major security benefits in diverse fields. Therefore, this land holding system is implemented using a blockchain architecture. In India main problems in traditional land holding system include space constraints, fraud in land registry, lack of uniformity and poor maintenance of land records, lack of single window title verification and investigation system, fear of destruction of records by force majeure events. Therefore, a blockchain is prepared to aid these problems in order to solve these problems we have analyzed, id...
International Journal of Current Science Research and Review, 2022
People’s lives have been profoundly impacted by the headway of innovation which has worked on the... more People’s lives have been profoundly impacted by the headway of innovation which has worked on their lives from each viewpoint. Clearly, innovation assumes a significant part in each circle of life and information stockpiling and sharing is a significant part of it. Current information sharing and storage devices depend on trusted third parties (TTP) and because of the contribution of third parties, such frameworks need straightforwardness, security, trust and strength. To solve these issues, this paper proposes a blockchain-based secure information sharing application by consolidating the highlights of IPFS and Ethereum. In this proposed scheme ethereum blockchain, decentralized storage, encryption and IPFS are combined to build an application that maximizes the technological resources and provide with an effective storage website ,Ethereum blockchain, decentralized capacity, encryption, and InterPlanetary File System are consolidated to assemble an application that boosts the innov...
... SUMAN MANN1, ANJANA GOSAIN2, SANGEETA SABHARWAL3 1Department of computer science, Maharaja su... more ... SUMAN MANN1, ANJANA GOSAIN2, SANGEETA SABHARWAL3 1Department of computer science, Maharaja surajmal institute of technology, Delhi 2Department of Information Technology, GGS Indraprastha University, Delhi ... This multidimensional is basically the Star schema ...
Journal of Information and Optimization Sciences, 2022
Abstract Many methods have been developed to protect web servers against attacks. Anomaly detecti... more Abstract Many methods have been developed to protect web servers against attacks. Anomaly detection methods rely on generic user models and application behavior, which interpret departures as indications of potentially dangerous behavior from the established pattern. However, due to a lack of evaluations and comparisons of various anomaly detection techniques, engineers may still decide which detection methods should not be used. Furthermore, even if engineers use an unusual detection technique, re-implementation will take a lifetime. We offer a comprehensive analysis and evaluation of six existing log-based detection techniques, including three monitored and three unchecked modes, as well as an open toolkit that allows for simple reuse, to address these problems. The different anomalies are detected with weighted PCA techniques. There are four datasets BGL, Liberty, Spirit & Thunderbird, which are used. The weighted PCA is compared with traditional KNN methods. The weighted PCA provided better results as compared to the KNN algorithm.
Breast cancer is the most prevalent form of cancer that can strike at any age; the higher the age... more Breast cancer is the most prevalent form of cancer that can strike at any age; the higher the age, the greater the risk. The presence of malignant tissue has become more frequent in women. Although medical therapy has improved breast cancer diagnostic and treatment methods, still the death rate remains high due to failure of diagnosing breast cancer in its early stages. A classification approach for mammography images based on nonsubsampled contourlet transform (NSCT) is proposed in order to investigate it. The proposed method uses multiresolution NSCT decomposition to the region of interest (ROI) of mammography images and then uses Z-moments for extracting features from the NSCT-decomposed images. The matrix is formed by the components that are extracted from the region of interest and are then subjected to singular value decomposition (SVD) in order to remove the essential features that can generalize globally. The method employs a support vector machine (SVM) classification algor...
International Journal of Environmental Science and Technology
The change in habits and lifestyle of citizens during health crisis like COVID-19 pandemic has re... more The change in habits and lifestyle of citizens during health crisis like COVID-19 pandemic has resulted in an unprecedented increase in the struggles for solid waste management across the globe. Not only underdeveloped and developing economies are struggling with the challenges posed by mounting piles of infectious waste but even developed countries are adversely affected in similar manner. The routine waste management strategies followed by various countries are overturned due extremely altered trends in the amount and type of waste generated by households and medical facilities. The aim of this paper is to study and list the best available waste management policies adopted by some developing, developed and underdeveloped economies. The listed case studies were selected due to some unique steps undertaken for solid waste disposal during pandemic. The findings revealed that the guidelines issued by WHO for waste management of corona virus infected waste were followed by these nations and certain additional preventive steps were taken. Due to unavailability of single framework as prescribed by international authorities, various sustainable steps taken by individual countries to curb the pandemic menace can be useful in the present context. Few of these measures can be permanently adopted at global level by other nations for handling the pandemic like situations efficiently in pandemic situations.
Computational and Mathematical Methods in Medicine, Apr 14, 2022
Critical ML or CML is a critical approach development of the standard ML (SML) procedure. Convent... more Critical ML or CML is a critical approach development of the standard ML (SML) procedure. Conventional ML (ML) is being used in radiology departments where complex neuroimages are discriminated using ML technology. Radiologists and researchers found that sole decision by the ML algorithms is not accurate enough to implement the treatment procedure. Thus, an intelligent decision is required further by the radiologists after evaluating the ML outcomes. The current research is based on the critical ML, where radiologists' critical thinking ability, IQ (intelligence quotient), and experience in radiology have been examined to understand how these factors affect the accuracy of neuroimaging discrimination. A primary quantitative survey has been carried out, and the data were analysed in IBM SPSS. The results showed that experience in works has a positive impact on neuroimaging discrimination accuracy. IQ and trained ML are also responsible for improving the accuracy as well. Thus, radiologists with more experience in that field are able to improve the discriminative and diagnostic capability of CML.
Resource management efficiency can be a beneficial step toward optimizing power consumption in so... more Resource management efficiency can be a beneficial step toward optimizing power consumption in software-hardware integrated systems. Languages such as C, C++, and Fortran have been extremely popular for dealing with optimization, memory management, and other resource management. We investigate novel algorithmic architectures capable of optimizing resource requirements and increasing energy efficiency. The experimental results obtained with C++ can be extended to other programming languages as well. We emphasize the inherent drawbacks of memory management operators. These operators are intended to be extremely generic in their application, just as the concept of dynamic memory is. As a result, they are unable to take advantage of the various optimization techniques and opportunities that specific use cases present. Each source code file is modeled after its own distinct memory usage pattern, which can be used to speed up memory management routines. Such concepts are frequently time-c...
Pandemics and epidemics have plagued humanity throughout history. The modern world faced one such... more Pandemics and epidemics have plagued humanity throughout history. The modern world faced one such devastating disease in 2019 called Coronavirus. As the world is still trying to recover from Coronavirus, an epidemic that might not see its end anytime soon. This study focuses on analyzing and predicting the future hospital admissions that arise due to Covid-19 .For this study, the choice of country is the United Kingdom. The data has been procured from reliable internet sources to carry out all necessary experiments. The data set contains daily hospitalisations due to Covid-19 in the United Kingdom. To carry out the time-series forecasting, the predictive model is built using a special Recurrent Neural Network, also known as Long Short-Term Memory (LSTM) . The final model was built using a Stacked LSTM to predict the number of hospitalisations due to Covid-19 that may arise in the United Kingdom for the next twenty days from the last day of the dataset used. The results of this stud...
This study proposes a novel glaucoma identification system from fundus images through the deep be... more This study proposes a novel glaucoma identification system from fundus images through the deep belief network (DBN) optimized by the elephant-herding optimization (EHO) algorithm. Initially, the input image undergoes the preprocessing steps of noise removal and enhancement processes, followed by optical disc (OD) and optical cup (OC) segmentation and extraction of structural, intensity, and textural features. Most discriminative features are then selected using the ReliefF algorithm and passed to the DBN for classification into glaucomatous or normal. To enhance the classification rate of the DBN, the DBN parameters are fine-tuned by the EHO algorithm. The model has experimented on public and private datasets with 7280 images, which attained a maximum classification rate of 99.4%, 100% specificity, and 99.89% sensitivity. The 10-fold cross validation reduced the misclassification and attained 98.5% accuracy. Investigations proved the efficacy of the proposed method in avoiding bias,...
In the modern world, due to the usage of high-power chemical-based cosmetics, climate change, and... more In the modern world, due to the usage of high-power chemical-based cosmetics, climate change, and other major factors, skin cancer has been increasing among individuals. Skin cancer is considered as the most common malignant disorder, and there are more than a million cases being recorded with this disease every year. Extensive studies have already been performed to identify the risk factors and causative agents for skin cancer, including lifestyle changes and eatery patterns among individuals. The most common type of skin cancer is classified into basal cell carcinoma and squamous cell carcinoma. The researcher intends to conduct the research with the primary goal of determining the important factors in blockchain technology in the treatment of skin cancer in senior people. The application of new technologies such as blockchain has enabled offering better promises to health care professionals in addressing skin cancer in a more effective manner. These tools supported in evaluating ...
Phishing is the most prominent cyber-crime that uses camouflaged e-mail as a weapon. In simple wo... more Phishing is the most prominent cyber-crime that uses camouflaged e-mail as a weapon. In simple words, it is defined as the strategy adopted by fraudsters in-order-to get private details from persons by professing to be from wellknown channels like offices, bank, or a government organization. In this era of modernization, electronic mails are accustomed globally as communiqué channel for both private and professional purposes. The particulars exchanged over emails are often confidential and sensitive for example info of bank statements, payment bills, debit-credit reports, and authentication data. This makes e-mails precious for hackers because they can exploit these details for maleficent intends. The main goal of the attackers is to acquire personal details by deceiving the e-mail recipient to click noxious link or download the attachment under false pretences. In the last few years, there is an exponential rise in cyber threats including the major ones, phishing e-mails have result in huge monetary and identity losses. Several models have been developed to separate ham and phished e-mails but attackers are always trying new methods to invade the privacy of the people. Hence, there is dire need to perpetually develop new models or to upgrade the existing ones. The focus of the paper is to elaborate that specifically centers around on both machinelearning (ML) and deep-learning (DL) approaches for detecting phishing e-mails. It shows comparative analysis and assessment of various DL and ML models that were proposed in the last few decades to classify phishing e-mails at different stages of crime in a systematic manner. This paper discusses the problem's concept, its explication, and the anticipated future directions.
International Journal of Current Science Research and Review
Blockchain has been found of great use in various sectors and this technology promises much more ... more Blockchain has been found of great use in various sectors and this technology promises much more because of the high level of security it provides and blockchain provides us trade without the need of any mediators so Land holding system seems to be a very promising area of interest. All the countries around the world are now implementing blockchain in the area of land registrations in India, we should also consider it as a viable option. The blockchain has provided major security benefits in diverse fields. Therefore, this land holding system is implemented using a blockchain architecture. In India main problems in traditional land holding system include space constraints, fraud in land registry, lack of uniformity and poor maintenance of land records, lack of single window title verification and investigation system, fear of destruction of records by force majeure events. Therefore, a blockchain is prepared to aid these problems in order to solve these problems we have analyzed, id...
International Journal of Current Science Research and Review, 2022
People’s lives have been profoundly impacted by the headway of innovation which has worked on the... more People’s lives have been profoundly impacted by the headway of innovation which has worked on their lives from each viewpoint. Clearly, innovation assumes a significant part in each circle of life and information stockpiling and sharing is a significant part of it. Current information sharing and storage devices depend on trusted third parties (TTP) and because of the contribution of third parties, such frameworks need straightforwardness, security, trust and strength. To solve these issues, this paper proposes a blockchain-based secure information sharing application by consolidating the highlights of IPFS and Ethereum. In this proposed scheme ethereum blockchain, decentralized storage, encryption and IPFS are combined to build an application that maximizes the technological resources and provide with an effective storage website ,Ethereum blockchain, decentralized capacity, encryption, and InterPlanetary File System are consolidated to assemble an application that boosts the innov...
... SUMAN MANN1, ANJANA GOSAIN2, SANGEETA SABHARWAL3 1Department of computer science, Maharaja su... more ... SUMAN MANN1, ANJANA GOSAIN2, SANGEETA SABHARWAL3 1Department of computer science, Maharaja surajmal institute of technology, Delhi 2Department of Information Technology, GGS Indraprastha University, Delhi ... This multidimensional is basically the Star schema ...
Journal of Information and Optimization Sciences, 2022
Abstract Many methods have been developed to protect web servers against attacks. Anomaly detecti... more Abstract Many methods have been developed to protect web servers against attacks. Anomaly detection methods rely on generic user models and application behavior, which interpret departures as indications of potentially dangerous behavior from the established pattern. However, due to a lack of evaluations and comparisons of various anomaly detection techniques, engineers may still decide which detection methods should not be used. Furthermore, even if engineers use an unusual detection technique, re-implementation will take a lifetime. We offer a comprehensive analysis and evaluation of six existing log-based detection techniques, including three monitored and three unchecked modes, as well as an open toolkit that allows for simple reuse, to address these problems. The different anomalies are detected with weighted PCA techniques. There are four datasets BGL, Liberty, Spirit & Thunderbird, which are used. The weighted PCA is compared with traditional KNN methods. The weighted PCA provided better results as compared to the KNN algorithm.
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Papers by Suman Mann