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Institution

ITM University, Gurgaon, Haryana

EducationGurgaon, India
About: ITM University, Gurgaon, Haryana is a education organization based out in Gurgaon, India. It is known for research contribution in the topics: Encryption & Cryptosystem. The organization has 749 authors who have published 1159 publications receiving 12997 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors have analyzed the enablers for implementing sustainable supply chain management (SSCM) into Indian industries and identified influential enabler for adopting SSCM.

265 citations

Journal ArticleDOI
TL;DR: This work presents a comprehensive overview of various feature selection methods and their inherent pros and cons, and analyzes adaptive classification systems and parallel classification systems for chronic disease prediction.

238 citations

Journal ArticleDOI
TL;DR: In this paper, a new hybrid approach by combining the Support Vector Machine (SVM) with Wavelet Transform (WT) algorithm is developed to predict horizontal global solar radiation for both daily and monthly mean scales for an Iranian coastal city.

225 citations

Journal ArticleDOI
TL;DR: This study presents a novel hybrid method for CAD diagnosis, including risk factor identification using correlation based feature subset (CFS) selection with particle swam optimization (PSO) search method and K-means clustering algorithms, which outperforms other techniques.
Abstract: Coronary artery disease (CAD) is caused by atherosclerosis in coronary arteries and results in cardiac arrest and heart attack. For diagnosis of CAD, angiography is used which is a costly time consuming and highly technical invasive method. Researchers are, therefore, prompted for alternative methods such as machine learning algorithms that could use noninvasive clinical data for the disease diagnosis and assessing its severity. In this study, we present a novel hybrid method for CAD diagnosis, including risk factor identification using correlation based feature subset (CFS) selection with particle swam optimization (PSO) search method and K-means clustering algorithms. Supervised learning algorithms such as multi-layer perceptron (MLP), multinomial logistic regression (MLR), fuzzy unordered rule induction algorithm (FURIA) and C4.5 are then used to model CAD cases. We tested this approach on clinical data consisting of 26 features and 335 instances collected at the Department of Cardiology, Indira Gandhi Medical College, Shimla, India. MLR achieves highest prediction accuracy of 88.4 %.We tested this approach on benchmarked Cleaveland heart disease data as well. In this case also, MLR, outperforms other techniques. Proposed hybridized model improves the accuracy of classification algorithms from 8.3 % to 11.4 % for the Cleaveland data. The proposed method is, therefore, a promising tool for identification of CAD patients with improved prediction accuracy.

161 citations

Journal ArticleDOI
TL;DR: A systematic review of research on management in the pharmaceutical supply chain (PSC) is presented in this paper, with a distinct focus on three levels of industrial interaction, which influence the final value delivered.

154 citations


Authors

Showing all 763 results

NameH-indexPapersCitations
S. K. Maurya371213488
Prem Vrat33694894
Kehar Singh301974555
Stefan Fischer301984477
Abhishek Jain291203556
Prabhata K. Swamee291503278
R. C. Mittal281072456
Ram Kumar Sharma251292243
Pramila Goyal23521524
B. K. Das221001879
Divya Agarwal221982020
Yugal Kumar2070847
Sudheer Ch20301336
Amparo Borrell20871155
Anil Kumar Yadav19541145
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20237
202221
2021115
2020111
2019140
2018130