Institution
Acropolis Technical Campus
About: Acropolis Technical Campus is a based out in . It is known for research contribution in the topics: Failure rate & Reliability (statistics). The organization has 25 authors who have published 40 publications receiving 255 citations.
Topics: Failure rate, Reliability (statistics), Cloud computing, Cloud computing security, The Internet
Papers
More filters
••
TL;DR: The proposed F2GP achieved a maximum accuracy of 99.63%, 99.51% and 100% and DGP achieves a recall of 100% for all the test cases, which shows that using a new fitness function for unbalanced data classification improves the performance of a classifier.
Abstract: Breast Cancer is a common disease and to prevent it, the disease must be identified at earlier stages. Available breast cancer datasets are unbalanced in nature, i.e. there are more instances of benign (non-cancerous) cases then malignant (cancerous) ones. Therefore, it is a challenging task for most machine learning (ML) models to classify between benign and malignant cases properly, even though they have high accuracy. Accuracy is not a good metric to assess the results of ML models on breast cancer dataset because of biased results. To address this issue, we use Genetic Programming (GP) and propose two fitness functions. First one is F2 score which focuses on learning more about the minority class, which contains more relevant information, the second one is a novel fitness function known as Distance score (D score) which learns about both the classes by giving them equal importance and being unbiased. The GP framework in which we implemented D score is named as D-score GP (DGP) and the framework implemented with F2 score is named as F2GP. The proposed F2GP achieved a maximum accuracy of 99.63%, 99.51% and 100% for 60-40, 70-30 partition schemes and 10 fold cross validation scheme respectively and DGP achieves a maximum accuracy of 99.63%, 98.5% and 100% in 60-40, 70-30 partition schemes and 10 fold cross validation scheme respectively. The proposed models also achieves a recall of 100% for all the test cases. This shows that using a new fitness function for unbalanced data classification improves the performance of a classifier.
80 citations
••
TL;DR: In this article, a methodology for reliability assessment of electrical distribution system accounting random repair time omission for each section has been described, which has been implemented on two distribution systems and complete reliability analysis with repair time omitted has been presented.
31 citations
••
TL;DR: In this paper, a component importance measure known as diagnostic importance factor (DIF) has been used for this purpose and a methodology has been developed to compute a newly framed weighted cumulative diagnostic importance factors for each feeder section which represents quantitatively relative significance for prioritization of maintenance activities.
22 citations
••
12 Nov 2012TL;DR: The aim of this paper is for the survey of the several utilization techniques and some security aspects which are used in cloud computing.
Abstract: The Cloud computing which performs the task of the computing and storage capacity for a service to provide the flexibility for users. The providers manage the infrastructure and platforms on which the applications run by user. It relies on the sharing of resources to achieve the coherency and scalability for the utilization. Cloud computing relies on the network as an elementary service. The aim of this paper is for the survey of the several utilization techniques and some security aspects which are used in cloud computing.
22 citations
••
TL;DR: A series of polycrystalline La0.85−xSmxK0.15MnO3 (x = 0.05, 0.1 and 0.15) have been synthesized by standard solid state reaction method to study effects of substituting La3+ by Sm3+ ion on the structural, electrical and magnetic properties as discussed by the authors.
19 citations
Authors
Showing all 25 results
Name | H-index | Papers | Citations |
---|---|---|---|
Abhinav Saxena | 37 | 101 | 4681 |
Rajesh Arya | 10 | 25 | 276 |
M.W. Shaikh | 8 | 12 | 188 |
Aditi Sakalle | 5 | 17 | 116 |
Prashant Lakkadwala | 3 | 8 | 45 |
Kailash Chandra Bandhu | 3 | 10 | 28 |
Parag Parandkar | 3 | 13 | 56 |
Uday Moghe | 2 | 2 | 19 |
Ankit Upadhyay | 2 | 3 | 21 |
A. Udawat | 1 | 5 | 1 |
Anand Gadwal | 1 | 1 | 2 |
Ajay Bhargava | 1 | 1 | 5 |
Jayesh Umre | 1 | 1 | 2 |
Mahesh Pophaley | 1 | 1 | 4 |
Akshita Sharma | 1 | 1 | 1 |