Institution
Universiti Teknologi Petronas
Education•Ipoh, Malaysia•
About: Universiti Teknologi Petronas is a education organization based out in Ipoh, Malaysia. It is known for research contribution in the topics: Adsorption & Ionic liquid. The organization has 6127 authors who have published 11284 publications receiving 119400 citations.
Topics: Adsorption, Ionic liquid, Catalysis, Membrane, Biomass
Papers published on a yearly basis
Papers
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TL;DR: In this article, rice straw extract (RSE) was used to reduce pitting corrosion by presenting small hysteresis loop via cyclic polarization measurement and the formation of ferric-RSE layer due to complexation was confirmed via surface analysis.
64 citations
TL;DR: In this paper, the authors reported a simultaneous improvement in CO2 permeability and selectivity employing novel metal organic frameworks (MOFs), namely NOTT-300 and Pebax®1657 as polymer matrix.
64 citations
TL;DR: In this paper, the authors compared the performance of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) for ozone generation in a Dielectric Barrier Discharge-Corona hybrid plasma microreactor.
64 citations
TL;DR: It was concluded that both training algorithms SCG and LM could be recommended for suspended sediment prediction using MLP networks and LM was the faster (1/7 of SCG convergence time) of the two algorithms.
Abstract: Estimation of suspended sediment discharge in rivers has a vital role in dealing with water resources problems and hydraulic structures. In this study, a Multilayer Perceptron (MLP) feed forward neural network with four different training algorithms was used to predict the suspended sediment discharge of a river (Pari River at Silibin) in Peninsular Malaysia. The training algorithms are Gradient Descent (GD), Gradient Descent with Momentum (GDM), Scaled Conjugate Gradient (SCG), and Levenberg Marquardt (LM). Different statistical measures, time of convergence and number of epochs to reach the required accuracy were used to evaluate the performance of training algorithms. The analysis showed that SCG and LM performed better than GD and GDM. While the performance of the superior algorithms (i.e., SCG and LM) is similar, LM required considerably shorter time of convergence. It was concluded that both training algorithms SCG and LM could be recommended for suspended sediment prediction using MLP networks. However, LM was the faster (1/7 of SCG convergence time) of the two algorithms.
64 citations
TL;DR: The local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues, and can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images.
64 citations
Authors
Showing all 6203 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Muhammad Imran | 94 | 3053 | 51728 |
| Muhammad Shahbaz | 92 | 1001 | 34170 |
| Muhammad Farooq | 92 | 1341 | 37533 |
| Markus P. Schlaich | 74 | 472 | 25674 |
| Abdul Basit | 74 | 570 | 20078 |
| Keat Teong Lee | 71 | 276 | 16745 |
| Abdul Latif Ahmad | 68 | 490 | 22012 |
| Cor J. Peters | 52 | 262 | 9472 |
| Suzana Yusup | 52 | 437 | 8997 |
| Muhammad Nadeem | 52 | 409 | 9649 |
| Umer Rashid | 51 | 381 | 10081 |
| Hamidi Abdul Aziz | 49 | 345 | 9083 |
| Serge Palacin | 45 | 201 | 8376 |
| Muhammad Awais | 43 | 272 | 6704 |
| Zakaria Man | 43 | 245 | 5301 |