R. Naik

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James Elkins

School of the Art Institute of Chicago

Mohammed Seyam

Mansoura University

Vinicius Garcia

Universidade Federal de Pernambuco

Holly Rogers

Goldsmiths, University of London

David Seamon

Kansas State University

Rohit De

Yale University

Shahliza Halim

Universiti Teknologi Malaysia - UTM

Rui Dias

Universidade de Coimbra

Tribeni Prasad Banerjee

West Bengal University Of Technology

Elena Navarro

University of Castilla-La Mancha

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Papers by R. Naik

Performance Analysis of Hybrid (supervised and unsupervised) method for multiclass data set

IOSR Journal of Computer Engineering, 2014

Due to the increasing demand for multivariate data analysis from the various application the dime... more Due to the increasing demand for multivariate data analysis from the various application the dimensionality reduction becomes an important task to represent the data in low dimensional space for the robust data representation. In this paper, multivariate data analyzed by using a new approach SVM and ICA to enhance the classification accuracy in a way that data can be present in more condensed form. Traditional methods are classified into two types namely standalone and hybrid method. Standalone method uses either supervised or unsupervised approach, whereas hybrid method uses both approaches. This paper consists of SVM (support vector machine) as supervised and ICA (Independent component analysis) as a unsupervised approach for the improvement of the classification on the basis of dimensionality reduction. SVM uses SRM (structural risk minimization) principle which is very effective over ERM (empirical risk minimization) which minimizes an upper bound on the expected risk, as opposed to ERM that minimizes the error on the training data, whereas ICA uses maximum independence maximization to improve performance. The perpendicular or right angel projection is used to avoid the redundancy and to improve the dimensionality reduction. At last step a classification algorithm is used to classify the data samples and classification accuracy is measured. Experiments are performed for various two classes as well as multiclass dataset and performance of hybrid, standalone approaches are compared.

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Instantaneous Utilization Based Scheduling Algorithms for Real Time Systems

ijcsit.com

This paper proposes a new novel scheduling algorithms to schedule periodic tasks for soft real ti... more This paper proposes a new novel scheduling algorithms to schedule periodic tasks for soft real time system. This is a planning based offline scheduler where tasks are scheduled on the basis of its instantaneous utilization. Here after every quantum of execution, instantaneous utilization of each task is calculated. Task which is having highest instantaneous utilization is scheduled to the processor. Since Instantaneous utilization factor(IUF) is temporarily variant factor, the priority of each task will vary continuously. Also It is often more desirable to complete some portions of every task rather than giving up completely the processing of some tasks. The Imprecise Computation Model was introduced to allow for the tradeoff of the quality of computations in favor of meeting the deadline constraints. It is observed that scheduling performance metrics such as schedulability, CPU utilization, context switching, response time and reliability are improved by this approach as compared to scheduling algorithms such as RM, EDF, LLF, MUF scheduling algorithms.

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Modified IUF Scheduling Algorithm for Real Time Systems

by Ramchandra Manthalkar and R. Naik

2010 3rd International Conference on Emerging Trends in Engineering and Technology, 2010

It is often more desirable to complete some portions of every task rather than giving up complete... more It is often more desirable to complete some portions of every task rather than giving up completely the processing of some tasks. The Imprecise Computation Model was introduced to allow for the trade-off of the quality of computations in favor of meeting the deadline constraints. This paper proposes an algorithm which is basically a planning based offline scheduling algorithm. In this model, a task is logically decomposed into two subtasks, mandatory and optional. The mandatory portion of each task is scheduled using instantaneous utilization and optional portion is scheduled using shortest job first. It is observed that scheduling performance metrics such as schedulability, CPU utilization, context switching, response time and reliability are improved as compared to scheduling algorithms such as RM, EDF, LLF, MUF, IUF and IRIS scheduling algorithms.

Performance Analysis of Hybrid (supervised and unsupervised) method for multiclass data set

IOSR Journal of Computer Engineering, 2014

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Instantaneous Utilization Based Scheduling Algorithms for Real Time Systems

ijcsit.com

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Modified IUF Scheduling Algorithm for Real Time Systems

by Ramchandra Manthalkar and R. Naik

2010 3rd International Conference on Emerging Trends in Engineering and Technology, 2010

R. Naik

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