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Innovation and Emerging Technologies is a peer-reviewed journal published by World Scientific, covering Additive Manufacturing and 3D Printing Technologies, Advanced machining processes and optimization, Advanced Surface Polishing Techniques.
| Publisher | World Scientific |
|---|---|
| Reference style | Superscript numbered (World Scientific) Superscript — small raised numerals in the text 1. Smith, A., Jones, B. & Lee, C. A representative article title. Innovation and Emerging Technologies 12, 45–58 (2023).
Formats any DOI in the closest standard style — Innovation and Emerging Technologies has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Additive Manufacturing and 3D Printing Technologies Advanced machining processes and optimization Advanced Surface Polishing Techniques Advanced Machining and Optimization Techniques Artificial Intelligence in Healthcare and Education |
| ISSN | 2737-5994 |
| Citation impact (2-yr) | 3.77 |
| h-index | 10 |
| i10-index | 12 |
| Total citations | 665 |
| Top institutions publishing here | Lovely Professional University |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Forecasts regarding the prices of energy commodities have long been significant to many market players. Our research examines the price of Brent crude oil on a daily basis in order to address the issue. The price series under investigation has significant financial ramifications, and the sample under investigation spans 10 years, from April 7, 2014…
Dental disease evaluation and clinical assessment are frequently accomplished through radiographic penetration. The difficulty of obtaining an accurate clinical diagnosis from radiographs rises due to the minimal mineral density change in demineralized tissue of tooth and gum disorders. Dental abnormalities may not be visible on radiographs until the demineralization is higher than 40%, according to…
The anaconda software required python code in order to run the utilized individual K-nearest neighbor (KNN), random forest regression (RFR), and linear regression (LR) models. The results show that RFR machine learning (ML) technique out of the other utilized models shows the best performance for a used dataset. The findings of this article indicate that…
This research study addresses the critical global health issue of heart disease (HD), emphasizing the importance of early detection for improving recovery outcomes. The authors have applied various machine learning (ML) algorithms, including logistic regression (LR), linear discriminant analysis (LDA), Gaussian naive bayes (GNB), support vector machine (SVM), and XGBoost (XGB) to classify the Statlog…
For investors and governments, predicting the price of energy security is a critical problem. This research examines the suitability of the nonlinear autoregressive neural network for this forecasting problem using a dataset of daily closing prices for the energy security index that was traded on the China Shanghai Stock Exchange between January 4, 2016, and…
