Papers by H.Parveen Sultana
IGI-Global
Humanscanbeadverselyaffectedbyexposuretoairpollutantsinambientair.Hence,health-base... more Humanscanbeadverselyaffectedbyexposuretoairpollutantsinambientair.Hence,health-based standardsandobjectivesforanumberofpollutantsintheairaresetbyeachcountry.Detectionand measurementofcontentsoftheatmospherearebecomingincreasinglyimportant.Carefulplanning ofmeasurementsisessential.Oneofthemajorfactorsthatinfluencetherepresentativenessofdata collectedisthelocationofmonitoringstations.Theplanningandsettingupofamonitoringstation arecomplexandincursahugeexpenditure.AnIoT-basedrealtimeairpollutionmonitoringsystem isproposedtomonitorthepollutionlevelsofvariouspollutantsinCoimbatorecity.Thegeographical areaisclassifiedasindustrial,residentialandtrafficzones.ThisarticleproposesanIoTsystemthat couldbedeployedatanylocationandstorethemeasuredvalueinaclouddatabase,performpollution analysis,anddisplaythepollutionlevelatanygivenlocation.
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Pleiades Publishing, 2018
Machine learning is used as an effective support system in health diagnosis which contains large ... more Machine learning is used as an effective support system in health diagnosis which contains large volume of data. More commonly, analyzing such a large volume of data consumes more resources and execution time. In addition, all the features present in the dataset do not support in achieving the solution of the given problem. Hence, there is a need to use an effective feature selection algorithm for finding the more important features that contribute more in diagnosing the diseases. The Particle Swarm Optimization (PSO) is one of the metaheuristic algorithms to find the best solution with less time. Nowadays, PSO algorithm is not only used to select the more significant features but also removes the irrelevant and redundant features present in the dataset. However, the traditional PSO algorithm has an issue in selecting the optimal weight to update the velocity and position of the particles. To overcome this issue, this paper presents a novel function for identifying optimal weights on the basis of population diversity function and tuning function. We have also proposed a novel fitness function for PSO with the help of Support Vector Machine (SVM). The objective of the fitness function is to minimize the number of attributes and increase the accuracy. The performance of the proposed PSO-SVM is compared with the various existing feature selection algorithms such as Info gain, Chi-squared, One attribute based, Consistency subset, Relief, CFS, Filtered subset, Filtered attribute, Gain ratio and PSO algorithm. The SVM classifier is also compared with several classifiers such as Naive Bayes, Random forest and MLP.
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Springer Berlin Heidelberg, 2019
According to the survey 17.5 million deaths are happened due to the cardiovascular disease that l... more According to the survey 17.5 million deaths are happened due to the cardiovascular disease that leads to create heart attack, chest pain and stroke. Based on the survey it clearly concludes that most of the people affected by heart problem that need to be identified in the earlier stage for eliminating the future risk in patient health. The importance of the heart disease detection process helps to create the earlier detection system for identifying heart problem by using machine learning and optimized techniques but the developed forecasting systems are difficult to predict the heart problems in an accurate manner with minimum time. So, hybridized Ruzzo-Tompa memetic based deep trained Neocognitron neural network is introduced to analyze the heart disease related features and predict the heart disease in earlier stage. First, heart disease data has been collected from UCI repository, dimensionality of the data is minimized by hybridized Ruzzo-Tompa memetic approach. After reducing the number of features, that are trained by deep learning approach which analyze the features using maximum number of hidden layers that used to predict heart disease features successfully while making the Neocognitron neural network classification. Further efficiency of the system is evaluated using MATLAB based simulation results.
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Springer Berlin Heidelberg, 2019
Now-a-days heart disease is one of the serious disease because most of the people affected by thi... more Now-a-days heart disease is one of the serious disease because most of the people affected by this disease that leads to create death. Due to the serious risk of this heart disease, it has been identified in the beginning stage for avoiding the risk factors. Then the earlier detection system has been created by utilizing optimized and hybridized techniques to recognize the heart disease in earlier stage. So, artificial gravitational cuckoo search algorithm along with particle bee optimized associative memory neural network is introduced to manage the features present in the earlier heart disease classification system. Initially , heart disease related information is collected from Heart Disease Data Set-UCI repository. The collected information is huge in dimension which is difficult to process, that reduces the efficiency of heart disease identification system. So, the dimensionality of the features are reduces according to the behavior of gravitational cuckoo search algorithm. The selected features are processed by above defined associative memory classifier. Then the efficiency of the system is evaluated with the help of MATLAB based experimental results. Keywords Heart disease · Artificial gravitational cuckoo search algorithm along with particle bee optimized associative memory neural network · Heart disease data set-UCI repository
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American Scientific Publishers, 2019
Network Security is the most important aspect for all products and services offered by networking... more Network Security is the most important aspect for all products and services offered by networking systems. The network density and usage in information systems, technical systems are humungous and is used by the entire world to provide connectivity from busiest hours to remote locations. Mission critical events, governmental organizations, information technology structures rely on continuous and smooth provision of network connection. This makes the basis of information security pillars-Confidentiality, which means that the data transferred between two users can be readable but should not be understandable, meaning it should be encrypted; Integrity, which focuses on the aspect of reliable message transfer preventing any kind of message tampering in the data transfer process; and finally Authentication and Availability, meaning that the user sending and receiving the data are genuine, and that the data is available, free from denial attacks.
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Papers by H.Parveen Sultana