2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)
This paper presents the performance analysis of Ad-hoc-on-Demand Distance Vector (AODV) and Secur... more This paper presents the performance analysis of Ad-hoc-on-Demand Distance Vector (AODV) and Secure Ad-hoc-on-Demand Distance Vector (SAODV) protocol for packets transfer and communication among the nodes using Support Vector Machine (SVM) technique. The comparative analysis of SAODV and AODV protocol are presented against blackhole attack for the parameters energy consumption, throughput, packet delivery ratio and end-to-end delay in ad hoc networks. A methodology is designed which lays rules based on learnings from the computations and estimations made at the time of packet transfer. It has been found that the proposed methodology gives promising results than the one which lays networking rules at the time of setting up the network.
2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018
The prediction of student performance helps the teaching learning process identify the direction ... more The prediction of student performance helps the teaching learning process identify the direction of student progression and take remedial measures to step up the performance of weak students before it is too late. Additionally it also assists in identifying students with great potential and cater to their intellectual needs. This works as a feedback mechanism as well as feed forward mechanism. The feedback mechanism. It is also useful as feedback mechanism in apprising guardians of student progression and as feed forward approach for improving student result. It enables effective and intelligent data mining of student result data to forecast their potential performance. The paper presents an adaptive neuro fuzzy inference system with back propagation for prediction of student performance progression based on trends of past performances. The model is developed MATLAB R2018a software and validated by real time data set comprising of results of mix of students of various higher educati...
JIMS8I � International Journal of Information Communication and Computing Technology, 2018
Data mining leading to discovery of predictive information from large databases is a powerful tec... more Data mining leading to discovery of predictive information from large databases is a powerful technology to obtain useful knowledge and apply for effective decision making. The huge data is generated with evolution of electronic and digital platforms in every field. The major challenge related to data management lies in healthcare sector due to increase in patients proportional to the population growth and change in lifestyle. The data analytics and big data are becoming trends to provide solution to all analytical problems that can be obtained by using machine learning techniques. Today, Cancer is evolving as one of the major attention seeking phenomenon in developed as well as in developing countries that may lead to death if not diagnosed at the early stage. The late diagnosis, and hence delayed treatment increase the risk for the survival. Thus, early detection to improve the cancer outcome is very critical. This study is intended towards early diagnosis of cancer using more efficient analytical techniques. Moreover, accuracy plays an important role in prediction to improve the quality of care, thereby increasing the survival rate. For this study, the datasets are extracted from UCI Machine Learning Repository prepared by University of Wisconsin Hospitals. For the diagnosis and classification process, K Nearest Neighbor (KNN) classifier is applied with different values of K variable, introducing the process called KNN Clustering. Later the performance of KNN is compared with K-Means clustering on the same datasets.
2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT), 2021
With achievements of Machine learning over the past years many computer networks and artificial i... more With achievements of Machine learning over the past years many computer networks and artificial intelligence actively using Machine learning architecture and its technology to improvise the performance of their approach for effective output. Machine learning plays great role in the field of wireless ad-hoc network as by providing the suitable environment to the routing protocols to make them react accordingly so that will have maximum throughput and parameters such as packet delivery ratio, hop-to-hop count, optimization of quality of service (QoS) will increased. In this paper, various types of Machine learning applied on different wireless Ad-hoc network are studied and how the performance parameters vary accordingly. A systematic approach is used to study all simulators which are utilized and evaluated by different protocols used in MANET, VANET. There is a need of a many other parameters to be studied and simulation used in Ad-hoc network which enables the users to ensure the optimization so that we can minimize the chances of failure of data and maximize the throughput after selecting best model of machine learning. This paper presents the futuristic anatomy of different machine learning models used in various protocols.
It has been seen that necessity is the mother of invention and human being fulfill all their requ... more It has been seen that necessity is the mother of invention and human being fulfill all their requirements by developing unbelievable things. Recently, people are taking advantage of detectors for extracting useful information. In this paper we discuss Multimedia Data Mining to perform above task and multimedia data categorization. With advancement in technology an outsized quantity of multimedia system information has been taken to analysis centers for learning various factors altogether. Associate approach was planned to use data mining for multimedia data is called Multimedia Data Mining. Multimedia Data Mining is pattern discovery, rule extraction and data acquisition from database. To extract data from multimedia database, some techniques are used in this research we are using Multimedia Data Mining to extract the patterns for above to problems. For this, two common terms exist. The first one is, the multimedia system information data should be segregated and emerge as objects a...
The paper below summarizes the basic methodology of association rules along with the mining assoc... more The paper below summarizes the basic methodology of association rules along with the mining association algorithms. The algorithms include the most basic Apriori algorithm along with other algorithms such as AprioriTid, AprioriHybrid and their comparison. KeywordsAssociation Rules, Mining, Apriori,Apriori TID,Apriori Hybrid, Algorithm..
This paper revisits the problem of active learning and decision making when the cost of labeling ... more This paper revisits the problem of active learning and decision making when the cost of labeling incurs cost and unlabeled data is available in abundance. In many real world applications large amounts of data are available but the cost of correctly labeling it prohibits its use. In many cases, where unlabeled data is available in abundance, active learning can be employed. In our proposed approach we will try to incorporate clustering into active learning algorithm and also data reduction is achieved through feature selection. The algorithm learns itself incrementally and will adjust clusters and select appropriate features as it explores more data points.
International Journal of Artificial Life Research, 2011
This paper revisits the problem of active learning and decision making when the cost of labeling ... more This paper revisits the problem of active learning and decision making when the cost of labeling incurs cost and unlabeled data is available in abundance. In many real world applications large amounts of data are available but the cost of correctly labeling it prohibits its use. In such cases, active learning can be employed. In this paper the authors propose rough set based clustering using active learning approach. The authors extend the basic notion of Hamming distance to propose a dissimilarity measure which helps in finding the approximations of clusters in the given data set. The underlying theoretical background for this decision is rough set theory. The authors have investigated our algorithm on the benchmark data sets from UCI machine learning repository which have shown promising results.
Global journal of computer science and technology, 2013
In recent years network security has become an important issue. Encryption has come up as a solut... more In recent years network security has become an important issue. Encryption has come up as a solution, and plays an important role in information security system. Many techniques are needed to protect the shared data. The present work focus on cryptography to secure the data while transmitting in the network. Firstly the data which is to be transmitted from sender to receiver in the network must be encrypted using the encryption algorithm in cryptography. Secondly, by using decryption technique the receiver can view the original data. In this paper we implemented three encrypt techniques like AES, DES and RSA algorithms and compared their performance of encrypt techniques based on the analysis of its stimulated time at the time of encryption and decryption. Experiments results are given to analyses the effectiveness of each algorithm.
Abstract: The aim of this paper is to discuss and analyze a new and innovative research challenge... more Abstract: The aim of this paper is to discuss and analyze a new and innovative research challenge on opinion mining. This research challenge has been developed in opinion analysis of social community and their opinions on different topic. In this paper we are meant to develop a system that can identify and analyze opinion as represented in the electronic text. People are more eager to express and share their views on any topic regarding day-to-day activities and social issues as well in this paper a precise method for predicting people sentiments is used that enable us to extract opinion from the interviews, survey and internet that predict reviews of each and every person, which could prove valuable for social growth and research. So, current scenario needs to be analyzed with the help of interviews, blogs/forums and natural language processing. The results further validate and support the main issue of paper. ________________________________________________________________________...
International Journal of Sociotechnology and Knowledge Development
This article describes how with the tremendous popularity in the usage of social media has led to... more This article describes how with the tremendous popularity in the usage of social media has led to the explosive growth in unstructured data available on various social networking sites. Sentiment analysis of textual data collected from such platforms has become an important research area. In this article, the sentiment classification approach which employs an emotion detection technique is presented. To identify the emotions this paper uses the NRC lexicon based approach for identifying polarity of emotions. A score is computed to quantify emotions obtained from NRC lexicon approach. The method proposed has been tested on twitter datasets of government policies and reforms, more about current NDA government initiatives in India. The polarity components apply and classify the tweets into eight predefined emotions. This article performs both quantitative and sentiment analysis processes with the objective of analyzing the opinion conveyed to each social content, assign a category (+ve...
2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)
This paper presents the performance analysis of Ad-hoc-on-Demand Distance Vector (AODV) and Secur... more This paper presents the performance analysis of Ad-hoc-on-Demand Distance Vector (AODV) and Secure Ad-hoc-on-Demand Distance Vector (SAODV) protocol for packets transfer and communication among the nodes using Support Vector Machine (SVM) technique. The comparative analysis of SAODV and AODV protocol are presented against blackhole attack for the parameters energy consumption, throughput, packet delivery ratio and end-to-end delay in ad hoc networks. A methodology is designed which lays rules based on learnings from the computations and estimations made at the time of packet transfer. It has been found that the proposed methodology gives promising results than the one which lays networking rules at the time of setting up the network.
2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018
The prediction of student performance helps the teaching learning process identify the direction ... more The prediction of student performance helps the teaching learning process identify the direction of student progression and take remedial measures to step up the performance of weak students before it is too late. Additionally it also assists in identifying students with great potential and cater to their intellectual needs. This works as a feedback mechanism as well as feed forward mechanism. The feedback mechanism. It is also useful as feedback mechanism in apprising guardians of student progression and as feed forward approach for improving student result. It enables effective and intelligent data mining of student result data to forecast their potential performance. The paper presents an adaptive neuro fuzzy inference system with back propagation for prediction of student performance progression based on trends of past performances. The model is developed MATLAB R2018a software and validated by real time data set comprising of results of mix of students of various higher educati...
JIMS8I � International Journal of Information Communication and Computing Technology, 2018
Data mining leading to discovery of predictive information from large databases is a powerful tec... more Data mining leading to discovery of predictive information from large databases is a powerful technology to obtain useful knowledge and apply for effective decision making. The huge data is generated with evolution of electronic and digital platforms in every field. The major challenge related to data management lies in healthcare sector due to increase in patients proportional to the population growth and change in lifestyle. The data analytics and big data are becoming trends to provide solution to all analytical problems that can be obtained by using machine learning techniques. Today, Cancer is evolving as one of the major attention seeking phenomenon in developed as well as in developing countries that may lead to death if not diagnosed at the early stage. The late diagnosis, and hence delayed treatment increase the risk for the survival. Thus, early detection to improve the cancer outcome is very critical. This study is intended towards early diagnosis of cancer using more efficient analytical techniques. Moreover, accuracy plays an important role in prediction to improve the quality of care, thereby increasing the survival rate. For this study, the datasets are extracted from UCI Machine Learning Repository prepared by University of Wisconsin Hospitals. For the diagnosis and classification process, K Nearest Neighbor (KNN) classifier is applied with different values of K variable, introducing the process called KNN Clustering. Later the performance of KNN is compared with K-Means clustering on the same datasets.
2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT), 2021
With achievements of Machine learning over the past years many computer networks and artificial i... more With achievements of Machine learning over the past years many computer networks and artificial intelligence actively using Machine learning architecture and its technology to improvise the performance of their approach for effective output. Machine learning plays great role in the field of wireless ad-hoc network as by providing the suitable environment to the routing protocols to make them react accordingly so that will have maximum throughput and parameters such as packet delivery ratio, hop-to-hop count, optimization of quality of service (QoS) will increased. In this paper, various types of Machine learning applied on different wireless Ad-hoc network are studied and how the performance parameters vary accordingly. A systematic approach is used to study all simulators which are utilized and evaluated by different protocols used in MANET, VANET. There is a need of a many other parameters to be studied and simulation used in Ad-hoc network which enables the users to ensure the optimization so that we can minimize the chances of failure of data and maximize the throughput after selecting best model of machine learning. This paper presents the futuristic anatomy of different machine learning models used in various protocols.
It has been seen that necessity is the mother of invention and human being fulfill all their requ... more It has been seen that necessity is the mother of invention and human being fulfill all their requirements by developing unbelievable things. Recently, people are taking advantage of detectors for extracting useful information. In this paper we discuss Multimedia Data Mining to perform above task and multimedia data categorization. With advancement in technology an outsized quantity of multimedia system information has been taken to analysis centers for learning various factors altogether. Associate approach was planned to use data mining for multimedia data is called Multimedia Data Mining. Multimedia Data Mining is pattern discovery, rule extraction and data acquisition from database. To extract data from multimedia database, some techniques are used in this research we are using Multimedia Data Mining to extract the patterns for above to problems. For this, two common terms exist. The first one is, the multimedia system information data should be segregated and emerge as objects a...
The paper below summarizes the basic methodology of association rules along with the mining assoc... more The paper below summarizes the basic methodology of association rules along with the mining association algorithms. The algorithms include the most basic Apriori algorithm along with other algorithms such as AprioriTid, AprioriHybrid and their comparison. KeywordsAssociation Rules, Mining, Apriori,Apriori TID,Apriori Hybrid, Algorithm..
This paper revisits the problem of active learning and decision making when the cost of labeling ... more This paper revisits the problem of active learning and decision making when the cost of labeling incurs cost and unlabeled data is available in abundance. In many real world applications large amounts of data are available but the cost of correctly labeling it prohibits its use. In many cases, where unlabeled data is available in abundance, active learning can be employed. In our proposed approach we will try to incorporate clustering into active learning algorithm and also data reduction is achieved through feature selection. The algorithm learns itself incrementally and will adjust clusters and select appropriate features as it explores more data points.
International Journal of Artificial Life Research, 2011
This paper revisits the problem of active learning and decision making when the cost of labeling ... more This paper revisits the problem of active learning and decision making when the cost of labeling incurs cost and unlabeled data is available in abundance. In many real world applications large amounts of data are available but the cost of correctly labeling it prohibits its use. In such cases, active learning can be employed. In this paper the authors propose rough set based clustering using active learning approach. The authors extend the basic notion of Hamming distance to propose a dissimilarity measure which helps in finding the approximations of clusters in the given data set. The underlying theoretical background for this decision is rough set theory. The authors have investigated our algorithm on the benchmark data sets from UCI machine learning repository which have shown promising results.
Global journal of computer science and technology, 2013
In recent years network security has become an important issue. Encryption has come up as a solut... more In recent years network security has become an important issue. Encryption has come up as a solution, and plays an important role in information security system. Many techniques are needed to protect the shared data. The present work focus on cryptography to secure the data while transmitting in the network. Firstly the data which is to be transmitted from sender to receiver in the network must be encrypted using the encryption algorithm in cryptography. Secondly, by using decryption technique the receiver can view the original data. In this paper we implemented three encrypt techniques like AES, DES and RSA algorithms and compared their performance of encrypt techniques based on the analysis of its stimulated time at the time of encryption and decryption. Experiments results are given to analyses the effectiveness of each algorithm.
Abstract: The aim of this paper is to discuss and analyze a new and innovative research challenge... more Abstract: The aim of this paper is to discuss and analyze a new and innovative research challenge on opinion mining. This research challenge has been developed in opinion analysis of social community and their opinions on different topic. In this paper we are meant to develop a system that can identify and analyze opinion as represented in the electronic text. People are more eager to express and share their views on any topic regarding day-to-day activities and social issues as well in this paper a precise method for predicting people sentiments is used that enable us to extract opinion from the interviews, survey and internet that predict reviews of each and every person, which could prove valuable for social growth and research. So, current scenario needs to be analyzed with the help of interviews, blogs/forums and natural language processing. The results further validate and support the main issue of paper. ________________________________________________________________________...
International Journal of Sociotechnology and Knowledge Development
This article describes how with the tremendous popularity in the usage of social media has led to... more This article describes how with the tremendous popularity in the usage of social media has led to the explosive growth in unstructured data available on various social networking sites. Sentiment analysis of textual data collected from such platforms has become an important research area. In this article, the sentiment classification approach which employs an emotion detection technique is presented. To identify the emotions this paper uses the NRC lexicon based approach for identifying polarity of emotions. A score is computed to quantify emotions obtained from NRC lexicon approach. The method proposed has been tested on twitter datasets of government policies and reforms, more about current NDA government initiatives in India. The polarity components apply and classify the tweets into eight predefined emotions. This article performs both quantitative and sentiment analysis processes with the objective of analyzing the opinion conveyed to each social content, assign a category (+ve...
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Papers by Prerna Mahajan