Dr Vandana is presently working in the Department of Computer Applications, C.C.S. University Meerut (India) with a vast teaching experience. She has obtained her Ph. D degree in ‘Fuzzy Set-Theoretic Approach to CPU Scheduling’ from CCS University Meerut(INDIA). She has contributed several research papers in various research journals of National
Many researchers considered fuzzy and intuitionistic fuzzy
parameters in the transportation probl... more Many researchers considered fuzzy and intuitionistic fuzzy parameters in the transportation problem, but we deal with intervalvalued intuitionistic fuzzy parameters, which is another type of uncertainty that covers the favourable as well as unfavourable cases. In a multi-objective transportation problem, it is difficult to find the optimal solution for all objectives simultaneously. So, we have used the Intuitionistic Fuzzy Goal Programming (IFGP) with deviational function dk (1 wk ) (where k w is fixed numerical weight for k d which decided the importance of highest acceptance level of th k objective relative to other objectives) to find the compromise optimal solution. In this paper, we extend the model proposed by Nomani M.A. et al. in 2016 for Multi-Objective Solid Transportation Problem (MOSTP) with interval-valued intuitionistic fuzzy cost. We applied this approach to find the solution of the Solid Transportation Problem (STP) with satisfying all the constraints. To find the compromise optimal solution for all objectives simultaneously, we apply a new IFGP approach. The main focus of the proposed approach is to minimize the all objectives simultaneously and to obtain the solution nearly closed to the lower bounds of objectives. A numerical example is being carried out in favour of the proposed algorithm.
This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (n... more This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have been developed so far. In the present article, we have developed a mediative fuzzy correlation technique based on the parameters for COVID-19 patients from different parts of India. The proposed mediative fuzzy correlation technique provides the relation between the increments of COVID-19 positive patients in terms of the passage of increment with respect to time. The peaks of infected cases in connection with the other condition are estimated from the available data. The mediative fuzzy logic mathematical model can be utilized to find a good fit or a contradictory model for any pandemic model. The proposed approach to the prediction in COVID-19 based on mediative fuzzy logic has produced promising results for the continuous contradictory prediction in India.
Time of arrival, size of CPU burst and priority are three major factors that are usually attached... more Time of arrival, size of CPU burst and priority are three major factors that are usually attached with a process which is submitted for execution. Several scheduling policies exist which use one or the other of these factors to place the submitted processes in appropriate order in the ready queue. Each of the existing schedulers has some positive and negative implications by way of assigning individual importance to any of the three factors. This work is an attempt to analyze the collective effect of time of arrival, size of CPU burst and priority of the process, through a logical combination of all the three. Fuzzy Better Job First (FBJF) scheduling algorithm logically integrates these three factors of a process and uses fuzzy ranking approach to determine the next most worthy job to be executed. The proposed policy thus enjoys advantages all the criteria to considerable extent.
International Journal of Advanced Science and Technology, 2020
Size of quantum is a key factor in round-robin scheduling. When the chosen quantum is very large,... more Size of quantum is a key factor in round-robin scheduling. When the chosen quantum is very large, the algorithm degenerates to FCFS, while too short quantum leads to increased overheads because of more numbers of context switching. This work intends to select a suitable quantum dynamically in every round. A dynamic weighting policy that assigns weight in proportion to the remaining CPU burst timewould keep on changing the weights of the process in every round.The fuzzy technique for assigning weights has been used by previous authors. Membership values in fuzzy sets are based only on the consideration of the favorable evidences;for this reason,it may prove to be inadequate to cover up all the uncertainties.Vague sets are characterized by two membership values: truth membership and false membership value. These are therefore better capable of obtaining the combined effect of favorable and unfavorable evidences together.The present paper deals with vague sets to assign the weights to the processes and computes the quantum dynamically in every round. Numerical computations have been carried out for different sets of processes and the results have also being compared with fuzzy-based round-robin and conventional round-robin techniques.
In an uncertain situation, data may present in continuous form or discrete form. We have
various... more In an uncertain situation, data may present in continuous form or discrete form. We have
various techniques to deal with continuous data in a realistic situation. However, when data are
in discrete form, the existing techniques are inadequate to deal with these situations, and these
techniques cannot provide the proper modulation for adequate analysis of the system. In order
to provide the proper acceleration to discrete data, we need an appropriate modulation technique
that can help us to handle unconditional boundedness on the technique and will operate like the
techniques used for continuous data with fractional variables. In this work, we developed an
intuitionistic fuzzy fractional knowledge-based expert system using unconditional and qualified
fuzzy propositions based on the Z-intuitionistic fuzzy fractional valuation probability density function.
In this proposed method, the discrete fractional variables will be converted into intuitionistic fuzzy
fractional numbers and then be used in our algorithm. The proposed Z-intuitionistic fuzzy fractional
valuation knowledge-based system can easily be applied in the medical field for the diagnosis of
diseases in a vague environment due to the ordered-pair characteristics of the Z-intuitionistic fuzzy
fractional valuation. In this study, we collected data of dengue patients, which included seven clinical
findings: Temperature, sugar, Pulse Rate (PR), age, cough, and Blood Pressure (BP).A numerical
example was also carried out to elaborate on the present technique. In addition, a comparative
study is discussed in this work. We also provide the managerial implications of the data, with the
limitations of the proposed technique presented at the end of this work.
This research paper aims to endeavours modified method of RSA algorithm so the more secure RSA al... more This research paper aims to endeavours modified method of RSA algorithm so the more secure RSA algorithm can be developed. RSA algorithm provides the security service to every user who is connected through the network. Many cryptographic algorithms are used to exchange the information over network. RSA cryptosystem algorithm is widely used cryptographic algorithm in network security but it has problem of integer's factorisation for small numbers. Researchers have proposed many modifications to improve the security of traditional RSA. In this research various modifications are presented and compared to figure out new approaches of RSA cryptosystem, which try to improve the security and speed up the time of key generation encryption and decryption process.
This work attempts to mathematically formulize the computation of waiting time of any process in ... more This work attempts to mathematically formulize the computation of waiting time of any process in a static n-process, CPU-bound round robin scheme. That in effect, can calculate other performance measures also. An improvement in the existing round robin algorithm has also been worked out that provides priority to processes nearing completion. The suggested approach uses two ready queues, wherein a process is returned to the second ready queue after the completion of its penultimate round. This policy reduces the average waiting time and increases the throughput, in comparison to the conventional round robin scheme, while maintaining the same level of CPU utilization and no substantial increase in the overheads. The mathematical formulation of this policy is transparent enough; it provides, for each process, the actual order of shifting to the second queue and also the order of termination.
Journal of International Academy of Physical Sciences (JIAPS), 2010
Order of arrival, CPU time requirement and priority are three important factors that are usually ... more Order of arrival, CPU time requirement and priority are three important factors that are usually attached with a process arriving for execution. Several algorithms have been developed to order the processes in ready queue in an attempt to minimize average waiting time, response time or increasing the throughput. Existing algorithms have some positive and negative effects by way of assigning individual importance to any of the three factors. Present work is an effort to analyze the collective effect of time of arrival, size of CPU burst and priority of the process, through a logical combination of all the three. Proposed approach is based on a suitable classification of the attributes and ranking the processes according to logically assigned weights. The policy thus enjoys some advantages of all the criteria.
The purpose of any scheduling algorithm is to arrange processes in ready queue in a manner to pro... more The purpose of any scheduling algorithm is to arrange processes in ready queue in a manner to produce efficient results in terms of average waiting time, throughput and fairness etc. For this purpose, a number of scheduling algorithms are in existence. SJF is one of them. Though it provides optimal results, yet it is difficult to estimate the processing time of a process needed for its implementation. Present paper modifies average exponential formula and suggests a new computation technique based on fuzzy approximation for knowing CPU requirement of a process.
Many researchers considered fuzzy and intuitionistic fuzzy
parameters in the transportation probl... more Many researchers considered fuzzy and intuitionistic fuzzy parameters in the transportation problem, but we deal with intervalvalued intuitionistic fuzzy parameters, which is another type of uncertainty that covers the favourable as well as unfavourable cases. In a multi-objective transportation problem, it is difficult to find the optimal solution for all objectives simultaneously. So, we have used the Intuitionistic Fuzzy Goal Programming (IFGP) with deviational function dk (1 wk ) (where k w is fixed numerical weight for k d which decided the importance of highest acceptance level of th k objective relative to other objectives) to find the compromise optimal solution. In this paper, we extend the model proposed by Nomani M.A. et al. in 2016 for Multi-Objective Solid Transportation Problem (MOSTP) with interval-valued intuitionistic fuzzy cost. We applied this approach to find the solution of the Solid Transportation Problem (STP) with satisfying all the constraints. To find the compromise optimal solution for all objectives simultaneously, we apply a new IFGP approach. The main focus of the proposed approach is to minimize the all objectives simultaneously and to obtain the solution nearly closed to the lower bounds of objectives. A numerical example is being carried out in favour of the proposed algorithm.
This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (n... more This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have been developed so far. In the present article, we have developed a mediative fuzzy correlation technique based on the parameters for COVID-19 patients from different parts of India. The proposed mediative fuzzy correlation technique provides the relation between the increments of COVID-19 positive patients in terms of the passage of increment with respect to time. The peaks of infected cases in connection with the other condition are estimated from the available data. The mediative fuzzy logic mathematical model can be utilized to find a good fit or a contradictory model for any pandemic model. The proposed approach to the prediction in COVID-19 based on mediative fuzzy logic has produced promising results for the continuous contradictory prediction in India.
Time of arrival, size of CPU burst and priority are three major factors that are usually attached... more Time of arrival, size of CPU burst and priority are three major factors that are usually attached with a process which is submitted for execution. Several scheduling policies exist which use one or the other of these factors to place the submitted processes in appropriate order in the ready queue. Each of the existing schedulers has some positive and negative implications by way of assigning individual importance to any of the three factors. This work is an attempt to analyze the collective effect of time of arrival, size of CPU burst and priority of the process, through a logical combination of all the three. Fuzzy Better Job First (FBJF) scheduling algorithm logically integrates these three factors of a process and uses fuzzy ranking approach to determine the next most worthy job to be executed. The proposed policy thus enjoys advantages all the criteria to considerable extent.
International Journal of Advanced Science and Technology, 2020
Size of quantum is a key factor in round-robin scheduling. When the chosen quantum is very large,... more Size of quantum is a key factor in round-robin scheduling. When the chosen quantum is very large, the algorithm degenerates to FCFS, while too short quantum leads to increased overheads because of more numbers of context switching. This work intends to select a suitable quantum dynamically in every round. A dynamic weighting policy that assigns weight in proportion to the remaining CPU burst timewould keep on changing the weights of the process in every round.The fuzzy technique for assigning weights has been used by previous authors. Membership values in fuzzy sets are based only on the consideration of the favorable evidences;for this reason,it may prove to be inadequate to cover up all the uncertainties.Vague sets are characterized by two membership values: truth membership and false membership value. These are therefore better capable of obtaining the combined effect of favorable and unfavorable evidences together.The present paper deals with vague sets to assign the weights to the processes and computes the quantum dynamically in every round. Numerical computations have been carried out for different sets of processes and the results have also being compared with fuzzy-based round-robin and conventional round-robin techniques.
In an uncertain situation, data may present in continuous form or discrete form. We have
various... more In an uncertain situation, data may present in continuous form or discrete form. We have
various techniques to deal with continuous data in a realistic situation. However, when data are
in discrete form, the existing techniques are inadequate to deal with these situations, and these
techniques cannot provide the proper modulation for adequate analysis of the system. In order
to provide the proper acceleration to discrete data, we need an appropriate modulation technique
that can help us to handle unconditional boundedness on the technique and will operate like the
techniques used for continuous data with fractional variables. In this work, we developed an
intuitionistic fuzzy fractional knowledge-based expert system using unconditional and qualified
fuzzy propositions based on the Z-intuitionistic fuzzy fractional valuation probability density function.
In this proposed method, the discrete fractional variables will be converted into intuitionistic fuzzy
fractional numbers and then be used in our algorithm. The proposed Z-intuitionistic fuzzy fractional
valuation knowledge-based system can easily be applied in the medical field for the diagnosis of
diseases in a vague environment due to the ordered-pair characteristics of the Z-intuitionistic fuzzy
fractional valuation. In this study, we collected data of dengue patients, which included seven clinical
findings: Temperature, sugar, Pulse Rate (PR), age, cough, and Blood Pressure (BP).A numerical
example was also carried out to elaborate on the present technique. In addition, a comparative
study is discussed in this work. We also provide the managerial implications of the data, with the
limitations of the proposed technique presented at the end of this work.
This research paper aims to endeavours modified method of RSA algorithm so the more secure RSA al... more This research paper aims to endeavours modified method of RSA algorithm so the more secure RSA algorithm can be developed. RSA algorithm provides the security service to every user who is connected through the network. Many cryptographic algorithms are used to exchange the information over network. RSA cryptosystem algorithm is widely used cryptographic algorithm in network security but it has problem of integer's factorisation for small numbers. Researchers have proposed many modifications to improve the security of traditional RSA. In this research various modifications are presented and compared to figure out new approaches of RSA cryptosystem, which try to improve the security and speed up the time of key generation encryption and decryption process.
This work attempts to mathematically formulize the computation of waiting time of any process in ... more This work attempts to mathematically formulize the computation of waiting time of any process in a static n-process, CPU-bound round robin scheme. That in effect, can calculate other performance measures also. An improvement in the existing round robin algorithm has also been worked out that provides priority to processes nearing completion. The suggested approach uses two ready queues, wherein a process is returned to the second ready queue after the completion of its penultimate round. This policy reduces the average waiting time and increases the throughput, in comparison to the conventional round robin scheme, while maintaining the same level of CPU utilization and no substantial increase in the overheads. The mathematical formulation of this policy is transparent enough; it provides, for each process, the actual order of shifting to the second queue and also the order of termination.
Journal of International Academy of Physical Sciences (JIAPS), 2010
Order of arrival, CPU time requirement and priority are three important factors that are usually ... more Order of arrival, CPU time requirement and priority are three important factors that are usually attached with a process arriving for execution. Several algorithms have been developed to order the processes in ready queue in an attempt to minimize average waiting time, response time or increasing the throughput. Existing algorithms have some positive and negative effects by way of assigning individual importance to any of the three factors. Present work is an effort to analyze the collective effect of time of arrival, size of CPU burst and priority of the process, through a logical combination of all the three. Proposed approach is based on a suitable classification of the attributes and ranking the processes according to logically assigned weights. The policy thus enjoys some advantages of all the criteria.
The purpose of any scheduling algorithm is to arrange processes in ready queue in a manner to pro... more The purpose of any scheduling algorithm is to arrange processes in ready queue in a manner to produce efficient results in terms of average waiting time, throughput and fairness etc. For this purpose, a number of scheduling algorithms are in existence. SJF is one of them. Though it provides optimal results, yet it is difficult to estimate the processing time of a process needed for its implementation. Present paper modifies average exponential formula and suggests a new computation technique based on fuzzy approximation for knowing CPU requirement of a process.
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parameters in the transportation problem, but we deal with intervalvalued
intuitionistic fuzzy parameters, which is another type of
uncertainty that covers the favourable as well as unfavourable cases. In
a multi-objective transportation problem, it is difficult to find the
optimal solution for all objectives simultaneously. So, we have used the
Intuitionistic Fuzzy Goal Programming (IFGP) with deviational
function dk (1 wk ) (where k w is fixed numerical weight for k d
which decided the importance of highest acceptance level
of th k objective relative to other objectives) to find the compromise
optimal solution. In this paper, we extend the model proposed by
Nomani M.A. et al. in 2016 for Multi-Objective Solid Transportation
Problem (MOSTP) with interval-valued intuitionistic fuzzy cost. We
applied this approach to find the solution of the Solid Transportation
Problem (STP) with satisfying all the constraints. To find the
compromise optimal solution for all objectives simultaneously, we
apply a new IFGP approach. The main focus of the proposed approach
is to minimize the all objectives simultaneously and to obtain the
solution nearly closed to the lower bounds of objectives. A numerical
example is being carried out in favour of the proposed algorithm.
various techniques to deal with continuous data in a realistic situation. However, when data are
in discrete form, the existing techniques are inadequate to deal with these situations, and these
techniques cannot provide the proper modulation for adequate analysis of the system. In order
to provide the proper acceleration to discrete data, we need an appropriate modulation technique
that can help us to handle unconditional boundedness on the technique and will operate like the
techniques used for continuous data with fractional variables. In this work, we developed an
intuitionistic fuzzy fractional knowledge-based expert system using unconditional and qualified
fuzzy propositions based on the Z-intuitionistic fuzzy fractional valuation probability density function.
In this proposed method, the discrete fractional variables will be converted into intuitionistic fuzzy
fractional numbers and then be used in our algorithm. The proposed Z-intuitionistic fuzzy fractional
valuation knowledge-based system can easily be applied in the medical field for the diagnosis of
diseases in a vague environment due to the ordered-pair characteristics of the Z-intuitionistic fuzzy
fractional valuation. In this study, we collected data of dengue patients, which included seven clinical
findings: Temperature, sugar, Pulse Rate (PR), age, cough, and Blood Pressure (BP).A numerical
example was also carried out to elaborate on the present technique. In addition, a comparative
study is discussed in this work. We also provide the managerial implications of the data, with the
limitations of the proposed technique presented at the end of this work.
parameters in the transportation problem, but we deal with intervalvalued
intuitionistic fuzzy parameters, which is another type of
uncertainty that covers the favourable as well as unfavourable cases. In
a multi-objective transportation problem, it is difficult to find the
optimal solution for all objectives simultaneously. So, we have used the
Intuitionistic Fuzzy Goal Programming (IFGP) with deviational
function dk (1 wk ) (where k w is fixed numerical weight for k d
which decided the importance of highest acceptance level
of th k objective relative to other objectives) to find the compromise
optimal solution. In this paper, we extend the model proposed by
Nomani M.A. et al. in 2016 for Multi-Objective Solid Transportation
Problem (MOSTP) with interval-valued intuitionistic fuzzy cost. We
applied this approach to find the solution of the Solid Transportation
Problem (STP) with satisfying all the constraints. To find the
compromise optimal solution for all objectives simultaneously, we
apply a new IFGP approach. The main focus of the proposed approach
is to minimize the all objectives simultaneously and to obtain the
solution nearly closed to the lower bounds of objectives. A numerical
example is being carried out in favour of the proposed algorithm.
various techniques to deal with continuous data in a realistic situation. However, when data are
in discrete form, the existing techniques are inadequate to deal with these situations, and these
techniques cannot provide the proper modulation for adequate analysis of the system. In order
to provide the proper acceleration to discrete data, we need an appropriate modulation technique
that can help us to handle unconditional boundedness on the technique and will operate like the
techniques used for continuous data with fractional variables. In this work, we developed an
intuitionistic fuzzy fractional knowledge-based expert system using unconditional and qualified
fuzzy propositions based on the Z-intuitionistic fuzzy fractional valuation probability density function.
In this proposed method, the discrete fractional variables will be converted into intuitionistic fuzzy
fractional numbers and then be used in our algorithm. The proposed Z-intuitionistic fuzzy fractional
valuation knowledge-based system can easily be applied in the medical field for the diagnosis of
diseases in a vague environment due to the ordered-pair characteristics of the Z-intuitionistic fuzzy
fractional valuation. In this study, we collected data of dengue patients, which included seven clinical
findings: Temperature, sugar, Pulse Rate (PR), age, cough, and Blood Pressure (BP).A numerical
example was also carried out to elaborate on the present technique. In addition, a comparative
study is discussed in this work. We also provide the managerial implications of the data, with the
limitations of the proposed technique presented at the end of this work.