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Rasht, Iran

Islamic Azad University of Langaroud is a campus of Islamic Azad University system in Iran.The university was established in 1988 by some professors of Tehran University of Medical science include Dr. Mir Mozafar Maysoumi who was the first President of the university.So far 16000 students graduated from university. Wikipedia.

Biparva P.,Islamic Azad University at Langaroud | Biparva P.,University of Mazandaran | Hadjmohammadi M.R.,University of Mazandaran
Clean - Soil, Air, Water | Year: 2011

The present paper proposes the application of multiwalled carbon nanotubes (MWCNTs) as a solid adsorbent for selective separation/preconcentration of silver(I) in water samples prior to flame atomic absorption spectrometry. The procedure is based on the solid phase extraction of Ag(I)-2-mercaptobenzothiazole chelate on MWCNTs. The elution step is carried out with 5mL of 2molL -1 HNO 3 in acetone solution at a flow rate of 1.0mLmin -1. The influences of the various analytical parameters including pH of the solution, eluent type, sample volume, flow rates of eluent, matrix ions were investigated for optimization of the presented procedure. Tests of addition/recovery for analyte ion in real samples were performed with satisfactory results. Preconcentration factor and limit of detection for Ag(I) were 160 and 0.21μgL -1, respectively. The synthesized MWCNT exhibited excellent stability in eluent solution and its adsorption capacity was 5.4mg of silver per gram of sorbent. The proposed method was successfully applied to trace silver determination in a variety of environmental water samples. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ranjbari E.,University of Mazandaran | Biparva P.,Islamic Azad University at Langaroud | Hadjmohammadi M.R.,University of Mazandaran
Talanta | Year: 2012

A sensitive, rapid and efficient method for the extraction of quercetin as well as its determination in honey and biological samples was developed using inverted dispersive liquid-liquid microextraction (IDLLME) and HPLC-UV. The extraction method is based on the application of an extracting solvent lighter than water in the ternary component solvent (aqueous solution: extracting solvent: disperser solvent) system. The extraction parameters such as type and volume of extracting and disperser solvent, pH of sample, stirring rate and extraction time were optimized. Under the optimal conditions (extracting solvent: 100 μL 1-octanol; disperser solvent: 300 μL acetonitrile; pH of sample: 4.5 and stirring rate: 1000 rpm) a linear calibration curve was obtained in the range of 0.5-1000 ng mL -1 with R 2 = 0.9993 (n = 10). The limits of detection and quantification were 0.26 and 0.78 ng mL -1, respectively. The extraction recovery was 97% and the preconcentration factor was 243. While the relative standard deviation for 25 ng mL -1 was 3.51 (n = 5), it was 2.12 (n = 5) for 500 ng mL -1 of quercetin. The method was successfully applied for the preconcentration and determination of quercetin in honey, urine and plasma samples. © 2011 Elsevier B.V. All rights reserved.

Vakil-Baghmisheh M.T.,University of Tabriz | Ahandani M.A.,Islamic Azad University at Langaroud
Artificial Intelligence Review | Year: 2014

Memetic algorithms have been devised to rectify the absence of a local search mechanism in evolutionary algorithms. This paper proposes a differentialmemetic algorithm (DMA). To this end, first we propose a differential bidirectional random search as a local search algorithm. Then, a randomized blending crossover (RBleX) is proposed which aimed to scatter the new born offspring more diversely in the whole search space. We devise our proposed DMA, by using the RBleX crossover in the GA, and including the DBRS local search algorithm. A comparison of the performance of the DMA and those of seven other evolutionary/memetic or hybrid algorithms reported in two different papers on numerous bechmark functions demonstrates better performance of proposed DMA algorithm in most of the cases.©Springer Science+Business Media B.V. 2011.

Rouhi S.,Islamic Azad University at Langaroud | Ansari R.,Guilan University
Physica E: Low-Dimensional Systems and Nanostructures | Year: 2012

In this article, an atomistic model is developed to study the buckling and vibration characteristics of single-layered graphene sheets (SLGSs). By treating SLGSs as spaceframe structures, in which the discrete nature of graphene sheets is preserved, they are modeled using three-dimensional elastic beam elements for the bonds. The elastic moduli of the beam elements are determined via a linkage between molecular mechanics and structural mechanics. Based on this model, the critical compressive forces and fundamental natural frequencies of single-layered graphene sheets with different boundary conditions and geometries are obtained and then compared. It is indicated that the compressive buckling force decreases when the graphene sheet aspect ratio increases. At low aspect ratios, the increase of aspect ratios will result in a significant decrease in the critical buckling load. It is also indicated that increasing aspect ratio at a given side length results in the convergence of buckling envelops associated with armchair and zigzag graphene sheets. The influence of boundary conditions will be studied for different geometries. It will be shown that the influence of boundary conditions is not significant for sufficiently large SLGSs. © 2011 Elsevier B.V. All rights reserved.

Alinia Ahandani M.,Islamic Azad University at Langaroud | Vakil Baghmisheh M.T.,University of Tabriz | Badamchi Zadeh M.A.,University of Tabriz | Ghaemi S.,University of Tabriz
Swarm and Evolutionary Computation | Year: 2012

Examination timetabling is a discrete, multi-objective and combinatorial optimization problem which tends to be solved with a cooperation of stochastic search approaches such as evolutionary algorithms (EAs) and heuristic methods such as sequential graph coloring heuristics. This research investigates the use of discrete particle swarm optimization (DPSO) for solving examination timetabling problem. A combination of mutation, specialist recombination operator and graph coloring heuristics are used to update position of particles in the DPSO. A new local search method, called two staged hill climbing, is proposed and is utilized to hybridize the DPSO algorithm. Three structures for the DPSO and three strategies to hybridize it are proposed. On one hand, since the proposed DPSO algorithms such as hyper-heuristics methods employ a strategy to manage a set of constructive low-level heuristics, they can be classified as hyper-heuristic systems and, on the other hand, the DPSO is a stochastic global optimization method from class of EAs. The proposed algorithms are tested on a set of Carter benchmark problems to set the parameters of algorithms and also to compare different methods. The obtained results demonstrate that the proposed hill climbing local search, in spite of its simplicity, has a better performance than original hill climbing method. Among different graph coloring heuristics, those of algorithms which employ the saturation degree heuristic lead to the better results. Also among different proposed algorithms, the first structure of DPSO and third strategy of hybridizing obtain a better performance than the other structures and strategies. In a later part of the comparative experiment, performance comparisons of the proposed algorithms with some other hyper-heuristic and EA methods are done. The obtained results confirm that the proposed hybrid algorithm has a better, or at least comparable, performance than other hyper-heuristic systems. Also it obtains the best results among hyper-heuristic systems on some problems. Also in comparison of other EAs, it has a completely comparable performance. © 2012 Elsevier B.V. All rights reserved.

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