A Multi-Criteria Group Decision Making Methodology Using Interval Type-2 Fuzzy Sets: Application to Water Resources Management

In this paper, a new fuzzy group decision-making methodology which determines and incorporates negotiation powers of decision makers is developed. The proposed method is based on a combination of interval type-2 fuzzy sets and a multi-criteria decision making (MCDM) model, namely TOPSIS. To examine the applicability of the proposed methodology, it is used for finding the best scenario of allocating water and reclaimed wastewater to domestic, agricultural, and industrial water sectors and restoring groundwater quantity and quality in the Varamin region located in Tehran metropolitan area in Iran. The results show that the selected scenario leads to an acceptable groundwater conservation level during a long-term planning horizon. Although the capital cost of this scenario is high, which leads to groundwater restoration during the 34-year planning horizon, it is determined as the best allocation scenario. This scenario also entails the second least pumping cost, due to less water allocation from the groundwater. To evaluate the results of the proposed methodology, they are compared with those obtained using some well-known interval type-2 decision-making approaches including arithmetic-based, TOPSIS-based, and likelihood-based comparison methods. The Spearman correlation coefficient shows that the obtained results generally concur with those of the other methods. It is also concluded that the proposed methodology gives more reasonable results by calculating and considering the negotiation powers of decision makers in an extended TOPSIS-based group decision-making model.

     

New evolution in two-way relay networks based on physical layer network coding

Telecommunication Systems - In this paper, a physical-layer network coding (PNC) method is offered for a two-way relay network with spatial modulation (SM) for source node and relay node. For this...     

The effects of storage time and sunlight on microplastic pollution in bottled mineral water

The microplastic particles (MPs) and effects of storage time and direct sunlight on the MPs in bottled mineral waters were investigated by three experiments conditions. The mean MPs concentration was 63.9 ± 38.9 MPs/L. Pellet forms, white/yellow colour and sizes < 100 μm were predominant MPs, accounted for 35.3%, 51% and 60.2% of the total MPs, respectively. Storage of bottled water under darkness and sunlight caused an increase of 1.5% and 2.5% of MPs pollution, respectively. Also, the estimated daily intake (EDI) of MPs was 2.1, 6.4 and 9.6 MPs/kg BW.day for adults, children and infants, respectively. It is concluded that high storage time and direct sunlight may lead to a greater MPs pollution in mineral water and also high human intake through drinking bottled water. Therefore, it is suggested to reduce the expiry date of the bottled mineral water and avoid sunlight contact before consumption.     

Facile synthesis and characterization of CdTiO<Subscript>3</Subscript> nanoparticles by Pechini sol–gel method

In this work, CdTiO₃ nanoparticles were synthesized through reaction between Cd(CH₃COO)₂.2H₂O, Ti(OC₄H₉)₄, trimesic acid as a new chelating agent and ethanol as solvent by Pechini sol–gel method. X-ray diffraction (XRD) patterns showed that CdTiO₃ nanostructures have rhombohedral structure with diameter of about 35.61 nm. The structure, morphology and size of CdTiO₃ nanoparticles were characterized by FT-IR, XRD, SEM and EDAX. The optical properties of the products were studied by DRS. Based on the results of experiments, it was found that temperature and time of calcination, pH and the solvent of reaction are important parameters for formation of CdTiO₃ nanoparticles. Utilizing trimesic acid (benzene-1,3,5-tricarboxylic acid) as a new chelating agent for preparation of CdTiO₃ nanostructures was initiative of this work.     

Application of LS-SVM strategy to estimate H2S loading capacity in different ionic liquids and alkanolamines

Favorable properties of aqueous solutions are improved with the addition of different materials for separation of hydrogen sulfide (H₂S). Also, equilibrium data and available equations for solubility estimation of this gas are only valid for specific solutions and limited ranges of temperature and pressure. In this regard, a machine learning model based on Support vector machine (SVM) algorithm is proposed and developed with mixtures containing different amines and ionic liquids to predict H₂S solubility over wide ranges of temperature (298–434.5 K), pressure (13–9319 kPa), overall mass concentration (3.82–100%) and mixture's apparent molecular weight (18.39–556.17 g/mol). The accuracy of the performance of this network was evaluated by regression analysis on calculated and experimental data, which had not been used in network training.     

Adsorptive desulfurization and denitrogenation of model fuel by mesoporous adsorbents (MSU-S and CoO-MSU-S)

Adsorption of heterocyclic sulfur- and nitrogen-containing compounds by mesostructure adsorbent (MSU-S) and its modified form with cobalt oxide is studied using model fuel. The results of characteristic tests (XRD, N₂ adsorption–desorption, FTIR, and SEM) indicate that CoO impregnation causes a negative impact on mesoporous structure, crystalline phase, and particle shape along with a positive effect on surface ion exchange. CoO modification increased the adsorption loadings of DBT and BT to about 33.6% and 45.7%, respectively. For nitrogen compounds adsorption with the model fuel, adsorption loadings of quinoline and carbazole increase by 6.7% and 8.6%, respectively. Data fitting for carbazole, DBT, and BT is achieved better by the Langmuir model than the Freundlich model, and the data of quinoline fitted very well to the Freundlich model for CoO-MSU-S.     

High Gain Modified Dual-Band and Dual-Circularly Polarized Array Antenna

Wireless Personal Communications - A novel design of double-layer dual-band circularly polarized array antennas (DDCPAAs) is presented in this paper. First, a DDCP single antenna is introduced as...     

Electrooxidation of formaldehyde as a fuel for fuel cells using Fe2+-nano-zeolite modified carbon paste electrode

This study aimed to investigate the application of nano ZSM-5 zeolite for preparation of modified carbone paste electrode for electrocatalytic oxidation of formaldehyde. The electrochemical behavior of modified carbon paste electrodes in the forms of Fe/FeZSM-5CPE and unmodified carbon paste electrode were studied using cyclic voltammetric and chronoamprometric techniques. The obtained results show that the modified carbon paste electrode (Fe/FeZSM-5CPE) is the suitable electrode for electrooxidation of formaldehyde in the acidic solution. The transfer coefficient and current density for formaldehyde were calculated 0.23 and 19.8 mA/cm², respectively. The rate constant for catalytic reaction was calculated as 3.6 × 10³ cm³ s^?1 mol^?1 via Cottrell equation.     

Simple size-controlled fabrication of Zn2SnO4 nanostructures and study of their behavior in dye sensitized solar cells

Zn₂SnO₄ nanostructures were obtained via facile and rapid co-precipitation approach in presence of amines with different long chain as a novel basic and capping agents. The effect of different amines such as NH₃, ethylenediamine, triethylenetetramine, tetraethylenepentamine on the size of Zn₂SnO₄ nanostructures were investigated. The results demonstrated that applying the appropriate amount of organic amine could be effective in particle size control. The obtained nanostructure products were specified by powder X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectra, scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX) and ultraviolet–visible (UV–vis) spectroscopy. Dye sensitized solar cells (DSSC) were created by the constructed electrodes as working electrode and then were studied by current density–voltage (J–V) curve. It was found that incorporating of TiO₂ nanoparticles to optimized Zn₂SnO₄ nanostructures has significant role on the constructed DSSCs photovoltaic properties.     

Extraction of caffeine and catechins using microwave-assisted and ultrasonic extraction from green tea leaves: an optimization study by the IV-optimal design

In this research, optimal conditions for extraction of caffeine and polyphenols were established from Iranian green tea leaves. In the first step, caffeine was extracted with efficacy about 86% versed to 4.5% of EGC + EGCG. The EGCG + EGC was extracted from partially decaffeinated green tea leaves through microwave-assisted extraction (MAE) and ultrasound-assisted extraction (USE) with efficiency levels of 95 and 85%, respectively. The best results for the MAE process were obtained with 7.8 min and three number of extraction cycles and for the USE process were as followed: time 57 min, temperature 65 °C, and the number of extraction cycles 3. The total phenol content values at the best conditions of MAE and the USE processes were 125 ± 5 and 96 ± 6 mg gallic acid/g DW. The 50% inhibition (IC₅₀) on 1,1-diphenyl-2-picrylhydrazyl (DPPH) were 56 and 66 mg/g of phenol for the MAE and USE processes.