Institution
Graduate University of Advanced Technology
Education•Kerman, Iran•
About: Graduate University of Advanced Technology is a education organization based out in Kerman, Iran. It is known for research contribution in the topics: Carbon paste electrode & Electrochemical gas sensor. The organization has 890 authors who have published 2169 publications receiving 31027 citations.
Topics: Carbon paste electrode, Electrochemical gas sensor, Cyclic voltammetry, Electrode, Differential pulse voltammetry
Papers
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TL;DR: The algorithm introduced in this paper utilizes a load balancing routine to maximize resources’ efficiency at execution time and performs task scheduling with the least makespan and cost.
Abstract: Cloud infrastructures are suitable environments for processing large scientific workflows. Nowadays, new challenges are emerging in the field of optimizing workflows such that it can meet user’s service quality requirements. The key to workflow optimization is the scheduling of workflow tasks, which is a famous NP-hard problem. Although several methods have been proposed based on the genetic algorithm for task scheduling in clouds, our proposed method is more efficient than other proposed methods due to the use of new genetic operators as well as modified genetic operators and the use of load balancing routine. Moreover, a solution obtained from a heuristic used as one of the initial population chromosomes and an efficient routine also used for generating the rest of the primary population chromosomes. An adaptive fitness function is used that takes into account both cost and makespan. The algorithm introduced in this paper utilizes a load balancing routine to maximize resources’ efficiency at execution time. The performance of the proposed algorithm is evaluated by comparing the results with state of the art algorithms of this field, and the results indicate that the proposed algorithm has remarkable superiority in comparison to other algorithms and performs task scheduling with the least makespan and cost.
43 citations
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15 Dec 2012-Materials Science and Engineering A-structural Materials Properties Microstructure and Processing
TL;DR: In this article, the accumulative roll bonding (ARB) process was used to produce Al/Cup composite using Al 1100 strips and Cu fine particles, and the microstructure and mechanical properties of the composites were studied by scanning electron microscopy (SEM), tensile test and the Vickers microhardness test.
Abstract: In the present work, accumulative roll bonding (ARB) process was used to produce Al/Cup composite using Al 1100 strips and Cu fine particles. Microstructure and mechanical properties of the composites were studied during various ARB cycles by scanning electron microscopy (SEM), tensile test and the Vickers micro-hardness test. The SEM results revealed that, as the ARB cycle increases the layer of Cu particles is broken which leads to generation of elongated dense Cu clusters. At higher strains, the size of elongated clusters reduces while their uniformity and sphericity increase. This microstructure changes leads to improving the hardness, strength and elongation during ARB process. Generally, the mechanical properties of Al/Cup composite are better than those of pure Al at the same cycle of ARB. The results also demonstrated that, the Cu reinforcement particles in the form of uniformly dispersed clusters improve simultaneously the strength and toughness of Al during the ARB process.
43 citations
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TL;DR: In this paper, a new Ta(V) metal-organic framework nanostructure with high surface area, significant porosity, and small size distribution is presented for CO2 adsorption.
43 citations
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TL;DR: The developed assimilated methodology shows the robustness of the proposed ensemble hybrid model in analyzing water quality index over monthly horizons that experts could evaluate the water quality of rivers more efficiently.
43 citations
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TL;DR: It was found that the S-M-MWCNT composite could be reused after successive Hg(II) removal without any loss of adsorption capacity and holds high potential in the treatment of Hg-contaminated wastewater samples.
Abstract: A sulfur-coated magnetic multi-walled carbon nanotube (S-M-MWCNT) composite was synthesized via coating a thin S layer on M-MWCNTs via a facile heating process. The prepared superparamagnetic adsorbent was employed for the uptake of mercury(II) (Hg(II)) from aqueous solutions and then magnetically separated without filtration or centrifugation steps. The adsorption of Hg(II) increased with increasing pH and reached a plateau value in the pH range 4.5–8.0. The adsorption kinetics followed the pseudo-second-order (PSO) model and equilibrium was reached within 3 h. The isotherm data obeyed the Langmuir isotherm model, and the maximum adsorption capacity of S-M-MWCNT adsorbent was acquired as 62.11 mg g−1. The adsorption of Hg(II) by the prepared composite is possibly controlled by the interaction between Hg(II) as a soft acid and elemental coated sulfur as a soft base. In addition, the coexist metal ions including copper(II) (Cu(II)), cadmium(II) (Cd(II)), cobalt(II) (Co(II)), lead(II) (Pb(II)), manganese(II) (Mn(II)), zinc(II) (Zn(II)), and chromium(III) (Cr(III)) had no significant effects on Hg(II) removal performance. It was found that the S-M-MWCNT composite could be reused after successive Hg(II) removal without any loss of adsorption capacity. Furthermore, the magnetic adsorbent holds high potential in the treatment of Hg-contaminated wastewater samples.
43 citations
Authors
Showing all 906 results
Name | H-index | Papers | Citations |
---|---|---|---|
Michael Wink | 83 | 938 | 32658 |
Hassan Karimi-Maleh | 63 | 245 | 12503 |
Hadi Beitollahi | 56 | 272 | 8023 |
Sayed Khatiboleslam Sadrnezhaad | 38 | 215 | 4959 |
Akbar Maleki | 36 | 78 | 3542 |
Alireza Goudarzi | 34 | 117 | 4065 |
Alireza Askarzadeh | 32 | 68 | 4369 |
Somayeh Tajik | 31 | 109 | 2602 |
Mohammad Najafzadeh | 30 | 60 | 1882 |
Daryoush Afzali | 29 | 111 | 2363 |
Mehdi Yoosefian | 27 | 66 | 1673 |
Masoud Torkzadeh-Mahani | 26 | 94 | 1687 |
Reza Mohammadinejad | 26 | 85 | 2454 |
Farshid Keynia | 24 | 68 | 2402 |
Mohammad Yaghoobi | 24 | 83 | 1847 |