CPTR: conditional probability tree based routing in opportunistic networks

In opportunistic networks due to the inconsistency of the nodes link, routing is carried out dynamically and we cannot use proactive routes. In these networks, nodes use opportunities gained based on store-carry-forward patterns to forward messages. Every node that receives a message when it encounters another node makes decision regarding the forwarding or not forwarding the node encountered. In some previous methods, the recognition of whether encounter with current node is considered as an appropriate opportunity or not has been carried out based on the comparison of the probability of carrier node and the node encountered. In these methods, if the message is delivered to the encountered node, a better opportunity would be lost. To fight with this challenge we have posed CPTR method by using conditional probability tree method through which in addition to the probability of the delivery of carrier and encountered nodes’ message delivery, the opportunities for after encounter will be involved in messages’ forwarding. Results of simulation showed that the proposed method can improve the ratio of delivery and delay of message delivery compared to other similar methods in networks with limited buffer.     

Zinc oxide nanoparticles: solvent-free synthesis,characterization and application as heterogeneous nanocatalyst for photodegradation of dye from aqueous phase

In present study, for the first time, ZnO nanoparticles have been synthesized via a simple, novel, solvent and template free solid-state thermal decomposition of the mixed Zn(NO₃)·6H₂O and cochineal powders as a novel starting reagent at 600?°C for 3 h. The as-prepared product was analyzed by XRD, EDS, SEM, TEM, FT-IR and DRS. Besides, the effect of cochineal powder on the morphology and particle size of ZnO nanoparticles was investigated. The results exhibited that cochineal powder prevents the sintering of nanoparticles and leads to formation of uniform particles. Moreover, the efficiency of ZnO nanoparticles as a photocatalyst for the decolorization of methylene orange (MO) has been evaluated and 90% degradation of MO was obtained after 120 min.     

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.     

Application of artificial neural network for vapor liquid equilibrium calculation of ternary system including ionic liquid: Water, ethanol and 1-butyl-3-methylimidazolium acetate

A feed forward three-layer artificial neural network (ANN) model was developed for VLE prediction of ternary systems including ionic liquid (IL) (water+ethanol+1-butyl-3- methyl-imidazolium acetate), in a relatively wide range of IL mass fractions up to 0.8, with the mole fractions of ethanol on IL-free basis fixed separately at 0.1, 0.2, 0.4, 0.6, 0.8, and 0.98. The output results of the ANN were the mole fraction of ethanol in vapor phase and the equilibrium temperature. The validity of the model was evaluated through a test data set, which were not employed in the training case of the network. The performance of the ANN model for estimating the mole fraction and temperature in the ternary system including IL was compared with the non-random-two-liquid (NRTL) and electrolyte non-random-two-liquid (eNRTL) models. The results of this comparison show that the ANN model has a superior performance in predicting the VLE of ternary systems including ionic liquid.     

Controller Design Using Ant Colony Algorithm for a Non-inverting Buck–Boost Chopper Based on a Detailed Average Model

In this article, the non-inverting buck–boost converter and its operation modes are scrutinized. The closed-loop stability of the converter in buck and boost modes is analyzed, and the necessity of using an appropriated controller is demonstrated. Then the application of an adapted ant colony optimization to design a feedback controller is proposed, and a controller based on its existing model is tuned. Simulation and experimental results obtained from the ant colony optimization designed controller are then compared with a controller designed with the classic method. Although the simulation and experimental results prove the efficiency of the proposed control approach, a significant difference between controller behavior in practice and simulation is obvious. Finding these differences, more detailed models, including all parasitic elements, in the buck and boost modes are derived. Applying the proposed model in controller design illustrates that the desired performance of the converter can be guaranteed with a simple proportional-integral (PI) controller. The suggested ant colony-based controller is again tuned based on the more detailed model, which improves the performance of the converter system even more. Furthermore, good agreement between analytical and experimental outputs validates the accuracy of the modeling and simulation.     

Surfactant-Assisted Dispersion of MWCNTs in Epoxy Resin Used in CFRP Strengthening Systems

The epoxy resin used as the bonding agent in carbon fiber-reinforced polymer (CFRP) strengthening systems was modified by the infusion of multiwalled carbon nanotubes (MWCNTs). Two types of surfactants, Triton X-100 and C₁₂E₈, were used to disperse the nanotubes in the epoxy resin employing ultrasonic mixing. Dynamic mechanical analysis and tensile tests were conducted to study the effect of the surfactant-assisted dispersion of nanotubes on the thermal and mechanical properties of epoxy composites. The morphology of the epoxy composites was interpreted using scanning electron microscopy (SEM). Moreover, the effect of surfactant treatment on the structure of nanotubes was investigated by Fourier transform infrared (FT-IR). Based on the experimental results, the tensile strength and the storage modulus of the epoxy resin were increased by 32% and 26%, respectively, by the addition of MWCNTs. This was attributed to the homogeneous dispersion of nanotubes in the epoxy resin according to the SEM images. Another reason for the enhancement in the tensile properties was the reinforced nanotube/epoxy interaction as a result of the surfactant anchoring effect which was proved by FT-IR. A moderate improvement in the glass transition temperature (T _g) was recorded for the composite fabricated using Triton X-100, which was due to the restricted molecular motions in the epoxy matrix. To characterize the temperature-dependent tensile behavior of the modified epoxy composites, tensile tests were conducted at elevated temperatures. It was revealed that the MWCNT modification using surfactant substantially improves the tensile performance of the epoxy adhesive at temperatures above the T _g of the neat epoxy.     

考虑相关性的间歇性分布式电源选址定容规划

节能减排背景下,以分布式风电和光伏为代表的间歇性分布式电源得到了快速发展。考虑风速、光照强度和负荷间的相关性,以年综合费最小为目标,利用机会约束规划方法建立了间歇性分布式电源选址定容规划模型。采用秩相关系数矩阵表征风速、光照强度和负荷间的相关性,利用拉丁超立方采样和Cholesky分解生成相关性样本矩阵。应用动态小生境差分进化算法对规划模型进行求解。IEEE 33节点配电网算例的仿真结果验证了模型的合理性。     

On the Performance of Phase I Dispersion Control Charts for Process Monitoring

Control charts are usually implemented in two phases: the retrospective phase (phase I) and the monitoring phase (phase II). The performance of any phase II control chart structure depends on the preciseness of the control limits obtained from the phase I analysis. In statistical process control, the performance of phase I dispersion charts has mainly been investigated for normal or contaminated normal distributions of the quality characteristic of interest. Little work has been carried out to investigate the performance of a wide range of possible phase I dispersion charts for processes following non‐normal distributions. The current study deals with the proper choice of a control chart for the evaluation of process dispersion in phase I. We have analyzed the performance of a wide range of dispersion control charts, including two distribution‐free structures. The performance of the control charts is evaluated in terms of probability to signal, under normal and non‐normal process setups. These results will be useful for quality control practitioners in their selection of a phase I control chart. Copyright © 2014 John Wiley & Sons, Ltd.