Dr. Kiranjit kaur - Academia.edu (original) (raw)

Dr. Kiranjit kaur

Related Authors

Wolfram Wingerath

Azka Mahmood

Hina Farooq

COMSATS Institute of Information Technology sahiwal

Geeta Pattun (Asst. Prof.)

Chaimae Asaad

Chaimae Asaad

University Mohamed V, Faculté Des Sciences Rabat Agdal

Niranjan Ray

Rick  Cattell

Wilson A Higashino

Miriam Capretz

Uploads

Papers by Dr. Kiranjit kaur

Research paper thumbnail of Partitioning Techniques in Cloud Data Storage: Review Paper

International Journal of Advanced Research in Computer Science, 2017

As there is large amount of data generated from various web applications which are difficult to m... more As there is large amount of data generated from various web applications which are difficult to manage in cloud databases. Solution to this problem is to partition the data. In this paper three techniques named Horizontal, vertical and workload driven partitioning are reviewed. The main focus of the paper is to compare these techniques on the bases of complexity, scalability, consistency and number of distributed transactions. It provides result, based on that we can choose the most relevant partitioning technique to store cloud data.

Research paper thumbnail of A Novel Method of Data Partitioning Using Genetic Algorithm Work Load Driven Approach Utilizing Machine Learning

Cognitive Computing in Human Cognition, 2020

Research paper thumbnail of Improving E-Learning with Neural Networks

E-Learning is the latest emerging technology in the field of innovative teaching and learning. It... more E-Learning is the latest emerging technology in the field of innovative teaching and learning. It provides a virtual class room with all the facilities of conventional and advanced methods of teaching. The success rate of implementation of e-learning technology can be vastly improved by the use of neural networks. Using neural networks the registered students can be classified on various factors viz. learning abilities, goal of study etc. and hence be provided suitable integrated environments for study. Neural networks can further be used for evaluation purpose. This paper discusses through a model how neural networks can be used to improve the e-learning environment.

Research paper thumbnail of Partitioning Techniques in Cloud Data Storage: Review Paper

International Journal of Advanced Research in Computer Science, 2017

As there is large amount of data generated from various web applications which are difficult to m... more As there is large amount of data generated from various web applications which are difficult to manage in cloud databases. Solution to this problem is to partition the data. In this paper three techniques named Horizontal, vertical and workload driven partitioning are reviewed. The main focus of the paper is to compare these techniques on the bases of complexity, scalability, consistency and number of distributed transactions. It provides result, based on that we can choose the most relevant partitioning technique to store cloud data.

Research paper thumbnail of A Novel Method of Data Partitioning Using Genetic Algorithm Work Load Driven Approach Utilizing Machine Learning

Cognitive Computing in Human Cognition, 2020

Research paper thumbnail of Improving E-Learning with Neural Networks

E-Learning is the latest emerging technology in the field of innovative teaching and learning. It... more E-Learning is the latest emerging technology in the field of innovative teaching and learning. It provides a virtual class room with all the facilities of conventional and advanced methods of teaching. The success rate of implementation of e-learning technology can be vastly improved by the use of neural networks. Using neural networks the registered students can be classified on various factors viz. learning abilities, goal of study etc. and hence be provided suitable integrated environments for study. Neural networks can further be used for evaluation purpose. This paper discusses through a model how neural networks can be used to improve the e-learning environment.

Log In