Cloud computing is the new architecture that fulfils the dreams of several researchers on central... more Cloud computing is the new architecture that fulfils the dreams of several researchers on centrally organized and accessed resources. When a request is made to the cloud service provider, it has to be executed by one among several available servers and load on servers need to be balanced. This paper provides efficient load balancing algorithm for cloud environments, and it combines the merits of divisible load balancing algorithm and weighted round robin algorithm. The simulation result shows that this method is efficient and the values of processing time and response time yields low values compared to other methods. Additionally this method also removes the drawbacks of traditional round robin methods.
Intelligent Computing and Innovation on Data Science, 2021
In recent years, associative classification is gaining wide popularity because of its accuracy. I... more In recent years, associative classification is gaining wide popularity because of its accuracy. It integrates two crucial data mining techniques, association, and variety. Many domains desire high accuracy, and the medical domain is one among them. Since cardiovascular diseases affect most people, a framework to detect heart attack at an early stage using associative classification is presented. Two medical datasets, viz. Kleev Land and UCI, have been used. The proposed method selects the important attributes using entropy measure, and these attributes are used to perform association rule mining. These rules become the initial population for the genetic algorithm. To classify the strong association rules, a genetic algorithm along with the traditional k-nearest neighbor algorithm is used. This classifier improves the overall accuracy approximately by 5% of classification, thereby eliminating redundancies. The performance of the proposed method is compared with other traditional classifiers. It shows that the proposed method enhances heart disease prediction, and it is better under various performance metrics, viz. accuracy, time, error rate, FP rate, etc.
Organization's crucial data are highly endangered due to several security attacks and threats. In... more Organization's crucial data are highly endangered due to several security attacks and threats. Intrusion is one among such type of threat. Intrusions are efforts that attempt to elude normal security mechanisms of computer system. Intrusion detection is the process of monitoring and analyzing the events arising in a computer network to identify security breaches. Intrusion Detection System is the most important tool in maintaining network's security. This paper provides an overview of Intrusion Detection System and helps reader gain some fundamental concepts and methodologies used by IDS. This paper also provides discussion about types of IDS, approaches and types of attacks in the network and intensive literature survey. Finally, comparison of several IDS methods with merits and demerits are also presented in the paper.
Poor contrast is the main problem for color images. Contrast of an image often gets degraded due ... more Poor contrast is the main problem for color images. Contrast of an image often gets degraded due to faults in image acquisition devices, transmission errors, poor lightning conditions, power interference, etc. Hence these images need enhancement. Contrast enhancement using Histogram Equalization is well suited for grey level images whereas for color images, it is a tedious one as color image contains more than one channel. In this paper, enhancing contrast of color images using modified contrast limited adaptive histogram equalization method is proposed. First the image is decomposed into R, G and B components. G component of the color image alone is taken for enhancement. By calculating Local Contrast Modification (LCM) function and objective function, a decision is made whether to increase or not the value of G value for a pixel in an image. Little amount of contrast stretching is also performed on the image. It is observed that modified CLAHE preserves brightness, enhances the contrast of the input image and produces natural looking output images.
International Journal of Computer Applications, 2012
Low contrast and poor quality are main problems in the production of images. By using the wavelet... more Low contrast and poor quality are main problems in the production of images. By using the wavelet transform and HIS color analysis, a new idea is proposed. Color images are usually converted to gray image first in traditional image enhancement algorithms. The detail information was easily lost and at the same time these algorithms enhance noise while they enhance image, which lead to the descent of information entropy. With the combination of the characteristics of multi-scale and multi-resolution of Daubechies wavelet transform and the predominance of histogram equalization, a novel method of color image enhancement based on hue invariability with characteristics of human visual color consciousness in HIS color pattern is presented here. The experimental results showed that this new algorithm can enhance color images effectively and cost less time.
International Journal of Computer Applications, 2014
This paper presents a novel approach which address contrast enhancement in color images. The wave... more This paper presents a novel approach which address contrast enhancement in color images. The wavelet transform decomposes an image into bands that vary in spatial frequency and orientation. The HSV color model is well suited for color image enhancement methods even though RGB color space is the predominant one. By using Daubechies D4 wavelet transformation and HSV color model, a novel method of color image enhancement based on luminance adjustment is proposed here. The proposed method not only enables approximating digital signals in a better way but also it approximates highly non-linear digital signals. The experimental results showed that this new method can enhance color images effectively.
International Journal of Advanced Research in Computer Science, 2013
Wavelet transform is an important mathematical tool with strong application in signal processing.... more Wavelet transform is an important mathematical tool with strong application in signal processing. From the mathematical point of view, many different wavelet transforms are developed, where orthogonal wavelet transforms are more important. The main idea is to transform filter characteristics to wavelet Daubechies D4 representation before ANN training. The technique used is a new methodology to a multi-resolution digital signal analysis by discrete wavelet transforms. Our proposed method is to implement approximation digital signal scheme using Daubechies D4 wavelets. The present technique exhibits a revised procedure of removing distortion (loss) generated from the approximated double length digital signal presented in. For highly nonlinear digital signal, the technique fails to approximate the signal but the proposed revised technique can approximate the signal. At the beginning, a short mathematical introduction of the Daubechies D4 transform is presented. The proposed method not only enables approximating digital signals in a better way but also it approximates highly nonlinear digital signals. Texture patterns from seed clone images are then analyzed through wavelet's Daubechies D4 algorithm which produces discrete frequency coefficients representing the extracted features. Previous work only utilized three statistical parameters representing these coefficients such as mean, variance and standard deviation as the inputs for designing an intelligent identification model for various rubber tree seed clones.
International Journal of Engineering Research & Technology, 2013
Poor contrast is the main problem for color images. Contrast of an image often gets degraded due ... more Poor contrast is the main problem for color images. Contrast of an image often gets degraded due to faults in image acquisition devices, transmission errors, poor lightning conditions, power interference, etc. Hence these images need enhancement. Contrast enhancement using Histogram Equalization is well suited for grey level images whereas for color images, it is a tedious one as color image contains more than one channel. In this paper, enhancing contrast of color images using modified contrast limited adaptive histogram equalization method is proposed. First the image is decomposed into R, G and B components. G component of the color image alone is taken for enhancement. By calculating Local Contrast Modification (LCM) function and objective function, a decision is made whether to increase or not the value of G value for a pixel in an image. Little amount of contrast stretching is also performed on the image. It is observed that modified CLAHE preserves brightness, enhances the contrast of the input image and produces natural looking output images.
Cloud computing is the new architecture that fulfils the dreams of several researchers on central... more Cloud computing is the new architecture that fulfils the dreams of several researchers on centrally organized and accessed resources. When a request is made to the cloud service provider, it has to be executed by one among several available servers and load on servers need to be balanced. This paper provides efficient load balancing algorithm for cloud environments, and it combines the merits of divisible load balancing algorithm and weighted round robin algorithm. The simulation result shows that this method is efficient and the values of processing time and response time yields low values compared to other methods. Additionally this method also removes the drawbacks of traditional round robin methods.
International Journal of Computer Applications , 2012
Low contrast and poor quality are main problems in the production of images. By using the wavelet... more Low contrast and poor quality are main problems in the production of images. By using the wavelet transform and HIS color analysis, a new idea is proposed. Color images are usually converted to gray image first in traditional image enhancement algorithms. The detail information was easily lost and at the same time these algorithms enhance noise while they enhance image, which lead to the descent of information entropy. With the combination of the characteristics of multi-scale and multi-resolution of Daubechies wavelet transform and the predominance of histogram equalization, a novel method of color image enhancement based on hue invariability with characteristics of human visual color consciousness in HIS color pattern is presented here. The experimental results showed that this new algorithm can enhance color images effectively and cost less time.
In recent years, associative classification is gaining wide popularity because of its accuracy. I... more In recent years, associative classification is gaining wide popularity because of its accuracy. It integrates two crucial data mining techniques, association, and variety. Many domains desire high accuracy, and the medical domain is one among them. Since cardiovascular diseases affect most people, a framework to detect heart attack at an early stage using associative classification is presented. Two medical datasets, viz. Kleev Land and UCI, have been used. The proposed method selects the important attributes using entropy measure, and these attributes are used to perform association rule mining. These rules become the initial population for the genetic algorithm. To classify the strong association rules, a genetic algorithm along with the traditional k-nearest neighbor algorithm is used. This classifier improves the overall accuracy approximately by 5% of classification, thereby eliminating redundancies. The performance of the proposed method is compared with other traditional classifiers. It shows that the proposed method enhances heart disease prediction, and it is better under various performance metrics, viz. accuracy, time, error rate, FP rate, etc.
nternational Journal of Computer Applications , 2014
This paper presents a novel approach which address contrast enhancement in color images. The wave... more This paper presents a novel approach which address contrast enhancement in color images. The wavelet transform decomposes an image into bands that vary in spatial frequency and orientation. The HSV color model is well suited for color image enhancement methods even though RGB color space is the predominant one. By using Daubechies D4 wavelet transformation and HSV color model, a novel method of color image enhancement based on luminance adjustment is proposed here. The proposed method not only enables approximating digital signals in a better way but also it approximates highly non-linear digital signals. The experimental results showed that this new method can enhance color images effectively.
Organization’s crucial data are highly endangered due to several security attacks and threats. In... more Organization’s crucial data are highly endangered due to several security attacks and threats. Intrusion is one among such type of threat. Intrusions are efforts that attempt to elude normal security mechanisms of computer system. Intrusion detection is the process of monitoring and analyzing the events arising in a computer network to identify security breaches. Intrusion Detection System is the most important tool in maintaining network’s security. This paper provides an overview of Intrusion Detection System and helps reader gain some fundamental concepts and methodologies used by IDS. This paper also provides discussion about types of IDS, approaches and types of attacks in the network and intensive literature survey. Finally, comparison of several IDS methods with merits and demerits are also presented in the paper.
Cloud computing is the new architecture that fulfils the dreams of several researchers on central... more Cloud computing is the new architecture that fulfils the dreams of several researchers on centrally organized and accessed resources. When a request is made to the cloud service provider, it has to be executed by one among several available servers and load on servers need to be balanced. This paper provides efficient load balancing algorithm for cloud environments, and it combines the merits of divisible load balancing algorithm and weighted round robin algorithm. The simulation result shows that this method is efficient and the values of processing time and response time yields low values compared to other methods. Additionally this method also removes the drawbacks of traditional round robin methods.
Intelligent Computing and Innovation on Data Science, 2021
In recent years, associative classification is gaining wide popularity because of its accuracy. I... more In recent years, associative classification is gaining wide popularity because of its accuracy. It integrates two crucial data mining techniques, association, and variety. Many domains desire high accuracy, and the medical domain is one among them. Since cardiovascular diseases affect most people, a framework to detect heart attack at an early stage using associative classification is presented. Two medical datasets, viz. Kleev Land and UCI, have been used. The proposed method selects the important attributes using entropy measure, and these attributes are used to perform association rule mining. These rules become the initial population for the genetic algorithm. To classify the strong association rules, a genetic algorithm along with the traditional k-nearest neighbor algorithm is used. This classifier improves the overall accuracy approximately by 5% of classification, thereby eliminating redundancies. The performance of the proposed method is compared with other traditional classifiers. It shows that the proposed method enhances heart disease prediction, and it is better under various performance metrics, viz. accuracy, time, error rate, FP rate, etc.
Organization's crucial data are highly endangered due to several security attacks and threats. In... more Organization's crucial data are highly endangered due to several security attacks and threats. Intrusion is one among such type of threat. Intrusions are efforts that attempt to elude normal security mechanisms of computer system. Intrusion detection is the process of monitoring and analyzing the events arising in a computer network to identify security breaches. Intrusion Detection System is the most important tool in maintaining network's security. This paper provides an overview of Intrusion Detection System and helps reader gain some fundamental concepts and methodologies used by IDS. This paper also provides discussion about types of IDS, approaches and types of attacks in the network and intensive literature survey. Finally, comparison of several IDS methods with merits and demerits are also presented in the paper.
Poor contrast is the main problem for color images. Contrast of an image often gets degraded due ... more Poor contrast is the main problem for color images. Contrast of an image often gets degraded due to faults in image acquisition devices, transmission errors, poor lightning conditions, power interference, etc. Hence these images need enhancement. Contrast enhancement using Histogram Equalization is well suited for grey level images whereas for color images, it is a tedious one as color image contains more than one channel. In this paper, enhancing contrast of color images using modified contrast limited adaptive histogram equalization method is proposed. First the image is decomposed into R, G and B components. G component of the color image alone is taken for enhancement. By calculating Local Contrast Modification (LCM) function and objective function, a decision is made whether to increase or not the value of G value for a pixel in an image. Little amount of contrast stretching is also performed on the image. It is observed that modified CLAHE preserves brightness, enhances the contrast of the input image and produces natural looking output images.
International Journal of Computer Applications, 2012
Low contrast and poor quality are main problems in the production of images. By using the wavelet... more Low contrast and poor quality are main problems in the production of images. By using the wavelet transform and HIS color analysis, a new idea is proposed. Color images are usually converted to gray image first in traditional image enhancement algorithms. The detail information was easily lost and at the same time these algorithms enhance noise while they enhance image, which lead to the descent of information entropy. With the combination of the characteristics of multi-scale and multi-resolution of Daubechies wavelet transform and the predominance of histogram equalization, a novel method of color image enhancement based on hue invariability with characteristics of human visual color consciousness in HIS color pattern is presented here. The experimental results showed that this new algorithm can enhance color images effectively and cost less time.
International Journal of Computer Applications, 2014
This paper presents a novel approach which address contrast enhancement in color images. The wave... more This paper presents a novel approach which address contrast enhancement in color images. The wavelet transform decomposes an image into bands that vary in spatial frequency and orientation. The HSV color model is well suited for color image enhancement methods even though RGB color space is the predominant one. By using Daubechies D4 wavelet transformation and HSV color model, a novel method of color image enhancement based on luminance adjustment is proposed here. The proposed method not only enables approximating digital signals in a better way but also it approximates highly non-linear digital signals. The experimental results showed that this new method can enhance color images effectively.
International Journal of Advanced Research in Computer Science, 2013
Wavelet transform is an important mathematical tool with strong application in signal processing.... more Wavelet transform is an important mathematical tool with strong application in signal processing. From the mathematical point of view, many different wavelet transforms are developed, where orthogonal wavelet transforms are more important. The main idea is to transform filter characteristics to wavelet Daubechies D4 representation before ANN training. The technique used is a new methodology to a multi-resolution digital signal analysis by discrete wavelet transforms. Our proposed method is to implement approximation digital signal scheme using Daubechies D4 wavelets. The present technique exhibits a revised procedure of removing distortion (loss) generated from the approximated double length digital signal presented in. For highly nonlinear digital signal, the technique fails to approximate the signal but the proposed revised technique can approximate the signal. At the beginning, a short mathematical introduction of the Daubechies D4 transform is presented. The proposed method not only enables approximating digital signals in a better way but also it approximates highly nonlinear digital signals. Texture patterns from seed clone images are then analyzed through wavelet's Daubechies D4 algorithm which produces discrete frequency coefficients representing the extracted features. Previous work only utilized three statistical parameters representing these coefficients such as mean, variance and standard deviation as the inputs for designing an intelligent identification model for various rubber tree seed clones.
International Journal of Engineering Research & Technology, 2013
Poor contrast is the main problem for color images. Contrast of an image often gets degraded due ... more Poor contrast is the main problem for color images. Contrast of an image often gets degraded due to faults in image acquisition devices, transmission errors, poor lightning conditions, power interference, etc. Hence these images need enhancement. Contrast enhancement using Histogram Equalization is well suited for grey level images whereas for color images, it is a tedious one as color image contains more than one channel. In this paper, enhancing contrast of color images using modified contrast limited adaptive histogram equalization method is proposed. First the image is decomposed into R, G and B components. G component of the color image alone is taken for enhancement. By calculating Local Contrast Modification (LCM) function and objective function, a decision is made whether to increase or not the value of G value for a pixel in an image. Little amount of contrast stretching is also performed on the image. It is observed that modified CLAHE preserves brightness, enhances the contrast of the input image and produces natural looking output images.
Cloud computing is the new architecture that fulfils the dreams of several researchers on central... more Cloud computing is the new architecture that fulfils the dreams of several researchers on centrally organized and accessed resources. When a request is made to the cloud service provider, it has to be executed by one among several available servers and load on servers need to be balanced. This paper provides efficient load balancing algorithm for cloud environments, and it combines the merits of divisible load balancing algorithm and weighted round robin algorithm. The simulation result shows that this method is efficient and the values of processing time and response time yields low values compared to other methods. Additionally this method also removes the drawbacks of traditional round robin methods.
International Journal of Computer Applications , 2012
Low contrast and poor quality are main problems in the production of images. By using the wavelet... more Low contrast and poor quality are main problems in the production of images. By using the wavelet transform and HIS color analysis, a new idea is proposed. Color images are usually converted to gray image first in traditional image enhancement algorithms. The detail information was easily lost and at the same time these algorithms enhance noise while they enhance image, which lead to the descent of information entropy. With the combination of the characteristics of multi-scale and multi-resolution of Daubechies wavelet transform and the predominance of histogram equalization, a novel method of color image enhancement based on hue invariability with characteristics of human visual color consciousness in HIS color pattern is presented here. The experimental results showed that this new algorithm can enhance color images effectively and cost less time.
In recent years, associative classification is gaining wide popularity because of its accuracy. I... more In recent years, associative classification is gaining wide popularity because of its accuracy. It integrates two crucial data mining techniques, association, and variety. Many domains desire high accuracy, and the medical domain is one among them. Since cardiovascular diseases affect most people, a framework to detect heart attack at an early stage using associative classification is presented. Two medical datasets, viz. Kleev Land and UCI, have been used. The proposed method selects the important attributes using entropy measure, and these attributes are used to perform association rule mining. These rules become the initial population for the genetic algorithm. To classify the strong association rules, a genetic algorithm along with the traditional k-nearest neighbor algorithm is used. This classifier improves the overall accuracy approximately by 5% of classification, thereby eliminating redundancies. The performance of the proposed method is compared with other traditional classifiers. It shows that the proposed method enhances heart disease prediction, and it is better under various performance metrics, viz. accuracy, time, error rate, FP rate, etc.
nternational Journal of Computer Applications , 2014
This paper presents a novel approach which address contrast enhancement in color images. The wave... more This paper presents a novel approach which address contrast enhancement in color images. The wavelet transform decomposes an image into bands that vary in spatial frequency and orientation. The HSV color model is well suited for color image enhancement methods even though RGB color space is the predominant one. By using Daubechies D4 wavelet transformation and HSV color model, a novel method of color image enhancement based on luminance adjustment is proposed here. The proposed method not only enables approximating digital signals in a better way but also it approximates highly non-linear digital signals. The experimental results showed that this new method can enhance color images effectively.
Organization’s crucial data are highly endangered due to several security attacks and threats. In... more Organization’s crucial data are highly endangered due to several security attacks and threats. Intrusion is one among such type of threat. Intrusions are efforts that attempt to elude normal security mechanisms of computer system. Intrusion detection is the process of monitoring and analyzing the events arising in a computer network to identify security breaches. Intrusion Detection System is the most important tool in maintaining network’s security. This paper provides an overview of Intrusion Detection System and helps reader gain some fundamental concepts and methodologies used by IDS. This paper also provides discussion about types of IDS, approaches and types of attacks in the network and intensive literature survey. Finally, comparison of several IDS methods with merits and demerits are also presented in the paper.
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Papers by Sadique Basha
type of threat. Intrusions are efforts that attempt to elude normal security mechanisms of computer system. Intrusion
detection is the process of monitoring and analyzing the events arising in a computer network to identify security breaches.
Intrusion Detection System is the most important tool in maintaining network’s security. This paper provides an overview of Intrusion Detection System and helps reader gain some fundamental concepts and methodologies used by IDS. This paper also provides discussion about types of IDS, approaches and types of attacks in the network and intensive literature survey. Finally, comparison of several IDS methods with merits and demerits are also presented in the paper.
type of threat. Intrusions are efforts that attempt to elude normal security mechanisms of computer system. Intrusion
detection is the process of monitoring and analyzing the events arising in a computer network to identify security breaches.
Intrusion Detection System is the most important tool in maintaining network’s security. This paper provides an overview of Intrusion Detection System and helps reader gain some fundamental concepts and methodologies used by IDS. This paper also provides discussion about types of IDS, approaches and types of attacks in the network and intensive literature survey. Finally, comparison of several IDS methods with merits and demerits are also presented in the paper.