Swati Hira - Academia.edu (original) (raw)

Papers by Swati Hira

Research paper thumbnail of An intelligent hybrid deep belief network model for predicting students employability

Research paper thumbnail of An Approach To Predict Coronavirus Disease (Covid-19) In India Using Arima Model

Bioscience Biotechnology Research Communications, 2020

Research paper thumbnail of A Novel Map Reduced Based Parallel Feature Selection and Extreme Learning for Micro Array Cancer Data Classification

Wireless Personal Communications

Research paper thumbnail of Microarray cancer classification using feature extraction-based ensemble learning method

International Journal of Data Analysis Techniques and Strategies

Research paper thumbnail of An automatic approach based on CNN architecture to detect Covid-19 disease from chest X-ray images

Applied Intelligence

Novel coronavirus (COVID-19) is started from Wuhan (City in China), and is rapidly spreading amon... more Novel coronavirus (COVID-19) is started from Wuhan (City in China), and is rapidly spreading among people living in other countries. Today, around 215 countries are affected by COVID-19 disease. WHO announced approximately number of cases 11,274,600 worldwide. Due to rapidly rising cases daily in the hospitals, there are a limited number of resources available to control COVID-19 disease. Therefore, it is essential to develop an accurate diagnosis of COVID-19 disease. Early diagnosis of COVID-19 patients is important for preventing the disease from spreading to others. In this paper, we proposed a deep learning based approach that can differentiate COVID-19 disease patients from viral pneumonia, bacterial pneumonia, and healthy (normal) cases. In this approach, deep transfer learning is adopted. We used binary and multi-class dataset which is categorized in four types for experimentation: (i) Collection of 728 X-ray images including 224 images with confirmed COVID-19 disease and 504 normal condition images (ii) Collection of 1428 X-ray images including 224 images with confirmed COVID-19 disease, 700 images with confirmed common bacterial pneumonia, and 504 normal condition images. (iii) Collections of 1442 X-ray images including 224 images with confirmed COVID-19 disease, 714 images with confirmed bacterial and viral pneumonia, and 504 images of normal conditions (iv) Collections of 5232 X-ray images including 2358 images with confirmed bacterial and 1345 with viral pneumonia, and 1346 images of normal conditions. In this paper, we have used nine convolutional neural network based architecture (AlexNet, GoogleNet, ResNet-50, Se-ResNet-50, DenseNet121, Inception V4, Inception ResNet V2, ResNeXt-50, and Se-ResNeXt-50). Experimental results indicate that the pre trained model Se-ResNeXt-50 achieves the highest classification accuracy of 99.32% for binary class and 97.55% for multi-class among all pre-trained models.

Research paper thumbnail of Mining precise cause and effect rules in large time series data of socio-economic indicators

SpringerPlus

Background A system such as mechanical, biological or social-economic system consists of independ... more Background A system such as mechanical, biological or social-economic system consists of independent components. These components influence one another to maintain their activity for the existence of a system in order to achieve the goal of the system. The system changes behavior when a component is changed or removed significantly. This motivates us to find the reason or cause behind fault and discover the cause parameters in explaining the interactions among the components of a system or process. The causal discovery indicates not only that the indicators are correlated, but also how changing a cause variable is expected to induce a change in an effect variable. For example, with analyzed cause-effect relationships, we can predict potential effects before taking any actions (causes), which is useful in preventing inaccurate decision or policy making in the social-economical system. Time series data can be used to extract delayed relationship between two variables, for example, "CO2 emission occurring at a place might cause air pollution at another place after some delay". These lagged relationships signify the time lag between the cause-effect parameters. Identifying lagged relationships

Research paper thumbnail of IPV4 and IPV6 based hybrid approach for spam and virus detection

International Journal of Engineering & Technology

The proposed email setup consist of multiple mail servers distributed at two levels to achieve de... more The proposed email setup consist of multiple mail servers distributed at two levels to achieve desirable email access performance. It is a well-established fact that 99% of the emails received over internet are either spam or contained viruses and such emails can be dropped at the first entry point of the Network. Thus, the first level in the proposed architecture has been taken as an email gateway which is equipped with antivirus and anti-spam software. Spam assassion is an open source freeware software for filtering of the spam emails. Perl based spamassassion id to CPU and Memory hungry for heavily loaded server thus this new arrangement would then overcome the Problem of slow Email access for users by detaching spamassassion from email repository servers. The second level of the servers with email repositories for users all the email servers used in this implementation would be Linux X86 servers. Virtualization technique presents a software interface to virtual machines that is ...

Research paper thumbnail of Recurrence Based Similarity Identification of Climate Data

Discrete Dynamics in Nature and Society

Climate change has become a challenging and emerging research problem in many research related ar... more Climate change has become a challenging and emerging research problem in many research related areas. One of the key parameters in analyzing climate change is to analyze temperature variations in different regions. The temperature variation in a region is periodic within the interval. Temperature variations, though periodic in nature, may vary from one region to another and such variations are mainly dependent on the location and altitude of the region and also on other factors like the nearness of sea and vegetation. In this paper, we analyze such periodic variations using recurrence plot (RP), cross recurrence plot (CRP), recurrence rate (RR), and correlation of probability of recurrence (CPR) methods to find similarities of periodic variations between and within climatic regions and to identify their connectivity trend. First, we test the correctness of our method by applying it on voice and heart rate data and then experimentation is performed on synthetic climate data of nine r...

Research paper thumbnail of Estimating the Similarities of G7 Countries Using Economic Parameters

Advances in Intelligent Systems and Computing, 2016

Research paper thumbnail of Data Analysis using Multidimensional Modeling, Statistical Analysis and Data Mining on Agriculture Parameters

Procedia Computer Science, 2015

Research paper thumbnail of An Application of Factor Analysis in the Evaluation of Country Economic Rank

Procedia Computer Science, 2015

The inharmonious of rural enterprise and regional economy development is an important reason to c... more The inharmonious of rural enterprise and regional economy development is an important reason to cause the imbalance of China regional economy development. Based on the data of" Agricultural statistics Yearbook"(2006), the paper carries on statistics and sorting to ...

Research paper thumbnail of Intelligent Multidimensional Modelling

PsycEXTRA Dataset, 2000

On-Line Analytical Processing (OLAP) systems considerably ease the process of analyzing business ... more On-Line Analytical Processing (OLAP) systems considerably ease the process of analyzing business data and have become widely used in industry. Such systems primarily employ multidimensional data models to structure their data. However, current multidimensional data models fall short in time and skills to model the complex data found in some real-world application domains. Multidimensional data Analysis is based on Measure, Dimensions and Hierarchies. Process to find them manually is very crucial and time consuming because large and complex data is involved across multiple regions, products, and employees. This paper presents an Intelligent Multidimensional modelling system which helps the modeller in building multidimensional model and provides working at logical level by hiding heterogeneousity of physical database. The paper proposes the process to identify Measures, Dimensions, and Hierarchies to generate multidimensional model.

Research paper thumbnail of Estimating the difference of agriculture productivity in ASIAN regions

International Journal of Engineering & Technology

Agriculture is the major sector in the economy of Asia. The aim of this paper is to identify the ... more Agriculture is the major sector in the economy of Asia. The aim of this paper is to identify the importance of agriculture in Asia continent. In this paper, we evaluate differences between and within regions of Asia (Eastern-Asia, South-Central Asia, South-East Asia, and Western Asia and Middle Asia) and their countries. We used five agriculture parameters (Agriculture Land, Cereal production, Machinery, Tractors, Cereal yield, Land under cereal production) which widely represent agriculture productivity of Asia. The means of all Asian regions and its countries are identically similar is considered as a hypothesis for agriculture parameters. We use One-way ANOVA (analysis of variance) technique for analysis. Further, Asian regions and countries are estimated to test the differences of the means between and within regions and countries of each Asian region. The results show that each Asian region and their countries are having different agriculture productivity for agriculture parame...

Research paper thumbnail of An intelligent hybrid deep belief network model for predicting students employability

Research paper thumbnail of An Approach To Predict Coronavirus Disease (Covid-19) In India Using Arima Model

Bioscience Biotechnology Research Communications, 2020

Research paper thumbnail of A Novel Map Reduced Based Parallel Feature Selection and Extreme Learning for Micro Array Cancer Data Classification

Wireless Personal Communications

Research paper thumbnail of Microarray cancer classification using feature extraction-based ensemble learning method

International Journal of Data Analysis Techniques and Strategies

Research paper thumbnail of An automatic approach based on CNN architecture to detect Covid-19 disease from chest X-ray images

Applied Intelligence

Novel coronavirus (COVID-19) is started from Wuhan (City in China), and is rapidly spreading amon... more Novel coronavirus (COVID-19) is started from Wuhan (City in China), and is rapidly spreading among people living in other countries. Today, around 215 countries are affected by COVID-19 disease. WHO announced approximately number of cases 11,274,600 worldwide. Due to rapidly rising cases daily in the hospitals, there are a limited number of resources available to control COVID-19 disease. Therefore, it is essential to develop an accurate diagnosis of COVID-19 disease. Early diagnosis of COVID-19 patients is important for preventing the disease from spreading to others. In this paper, we proposed a deep learning based approach that can differentiate COVID-19 disease patients from viral pneumonia, bacterial pneumonia, and healthy (normal) cases. In this approach, deep transfer learning is adopted. We used binary and multi-class dataset which is categorized in four types for experimentation: (i) Collection of 728 X-ray images including 224 images with confirmed COVID-19 disease and 504 normal condition images (ii) Collection of 1428 X-ray images including 224 images with confirmed COVID-19 disease, 700 images with confirmed common bacterial pneumonia, and 504 normal condition images. (iii) Collections of 1442 X-ray images including 224 images with confirmed COVID-19 disease, 714 images with confirmed bacterial and viral pneumonia, and 504 images of normal conditions (iv) Collections of 5232 X-ray images including 2358 images with confirmed bacterial and 1345 with viral pneumonia, and 1346 images of normal conditions. In this paper, we have used nine convolutional neural network based architecture (AlexNet, GoogleNet, ResNet-50, Se-ResNet-50, DenseNet121, Inception V4, Inception ResNet V2, ResNeXt-50, and Se-ResNeXt-50). Experimental results indicate that the pre trained model Se-ResNeXt-50 achieves the highest classification accuracy of 99.32% for binary class and 97.55% for multi-class among all pre-trained models.

Research paper thumbnail of Mining precise cause and effect rules in large time series data of socio-economic indicators

SpringerPlus

Background A system such as mechanical, biological or social-economic system consists of independ... more Background A system such as mechanical, biological or social-economic system consists of independent components. These components influence one another to maintain their activity for the existence of a system in order to achieve the goal of the system. The system changes behavior when a component is changed or removed significantly. This motivates us to find the reason or cause behind fault and discover the cause parameters in explaining the interactions among the components of a system or process. The causal discovery indicates not only that the indicators are correlated, but also how changing a cause variable is expected to induce a change in an effect variable. For example, with analyzed cause-effect relationships, we can predict potential effects before taking any actions (causes), which is useful in preventing inaccurate decision or policy making in the social-economical system. Time series data can be used to extract delayed relationship between two variables, for example, "CO2 emission occurring at a place might cause air pollution at another place after some delay". These lagged relationships signify the time lag between the cause-effect parameters. Identifying lagged relationships

Research paper thumbnail of IPV4 and IPV6 based hybrid approach for spam and virus detection

International Journal of Engineering & Technology

The proposed email setup consist of multiple mail servers distributed at two levels to achieve de... more The proposed email setup consist of multiple mail servers distributed at two levels to achieve desirable email access performance. It is a well-established fact that 99% of the emails received over internet are either spam or contained viruses and such emails can be dropped at the first entry point of the Network. Thus, the first level in the proposed architecture has been taken as an email gateway which is equipped with antivirus and anti-spam software. Spam assassion is an open source freeware software for filtering of the spam emails. Perl based spamassassion id to CPU and Memory hungry for heavily loaded server thus this new arrangement would then overcome the Problem of slow Email access for users by detaching spamassassion from email repository servers. The second level of the servers with email repositories for users all the email servers used in this implementation would be Linux X86 servers. Virtualization technique presents a software interface to virtual machines that is ...

Research paper thumbnail of Recurrence Based Similarity Identification of Climate Data

Discrete Dynamics in Nature and Society

Climate change has become a challenging and emerging research problem in many research related ar... more Climate change has become a challenging and emerging research problem in many research related areas. One of the key parameters in analyzing climate change is to analyze temperature variations in different regions. The temperature variation in a region is periodic within the interval. Temperature variations, though periodic in nature, may vary from one region to another and such variations are mainly dependent on the location and altitude of the region and also on other factors like the nearness of sea and vegetation. In this paper, we analyze such periodic variations using recurrence plot (RP), cross recurrence plot (CRP), recurrence rate (RR), and correlation of probability of recurrence (CPR) methods to find similarities of periodic variations between and within climatic regions and to identify their connectivity trend. First, we test the correctness of our method by applying it on voice and heart rate data and then experimentation is performed on synthetic climate data of nine r...

Research paper thumbnail of Estimating the Similarities of G7 Countries Using Economic Parameters

Advances in Intelligent Systems and Computing, 2016

Research paper thumbnail of Data Analysis using Multidimensional Modeling, Statistical Analysis and Data Mining on Agriculture Parameters

Procedia Computer Science, 2015

Research paper thumbnail of An Application of Factor Analysis in the Evaluation of Country Economic Rank

Procedia Computer Science, 2015

The inharmonious of rural enterprise and regional economy development is an important reason to c... more The inharmonious of rural enterprise and regional economy development is an important reason to cause the imbalance of China regional economy development. Based on the data of" Agricultural statistics Yearbook"(2006), the paper carries on statistics and sorting to ...

Research paper thumbnail of Intelligent Multidimensional Modelling

PsycEXTRA Dataset, 2000

On-Line Analytical Processing (OLAP) systems considerably ease the process of analyzing business ... more On-Line Analytical Processing (OLAP) systems considerably ease the process of analyzing business data and have become widely used in industry. Such systems primarily employ multidimensional data models to structure their data. However, current multidimensional data models fall short in time and skills to model the complex data found in some real-world application domains. Multidimensional data Analysis is based on Measure, Dimensions and Hierarchies. Process to find them manually is very crucial and time consuming because large and complex data is involved across multiple regions, products, and employees. This paper presents an Intelligent Multidimensional modelling system which helps the modeller in building multidimensional model and provides working at logical level by hiding heterogeneousity of physical database. The paper proposes the process to identify Measures, Dimensions, and Hierarchies to generate multidimensional model.

Research paper thumbnail of Estimating the difference of agriculture productivity in ASIAN regions

International Journal of Engineering & Technology

Agriculture is the major sector in the economy of Asia. The aim of this paper is to identify the ... more Agriculture is the major sector in the economy of Asia. The aim of this paper is to identify the importance of agriculture in Asia continent. In this paper, we evaluate differences between and within regions of Asia (Eastern-Asia, South-Central Asia, South-East Asia, and Western Asia and Middle Asia) and their countries. We used five agriculture parameters (Agriculture Land, Cereal production, Machinery, Tractors, Cereal yield, Land under cereal production) which widely represent agriculture productivity of Asia. The means of all Asian regions and its countries are identically similar is considered as a hypothesis for agriculture parameters. We use One-way ANOVA (analysis of variance) technique for analysis. Further, Asian regions and countries are estimated to test the differences of the means between and within regions and countries of each Asian region. The results show that each Asian region and their countries are having different agriculture productivity for agriculture parame...