A novel frequency-selective metamaterial to improve helix antenna

A novel frequency-selective metamaterial with negative permittivity and permeability for improving directivity and gain of a helix antenna is presented in this paper.The proposed metamaterial is composed of two Z-shape resonators printed on opposite sides of a dielectric substrate.Two forms of multilayered cells are found to be suitable for antennas and waveguides applications.In addition,a new method of designing a metamaterial-based helix antenna is presented with high directivity and gain.A comparison on radiation properties is given between the conventional and the new metamaterial-based helix antennas.Two comparisons on radiation properties are performed:(1) the effect of proposed Z-structure on monopole,dipole,and helix antennas;(2) the effect of OE3,split-ring resonator (SRR),and proposed Z-structure unit cells on the performance of helix antennas.The results show improvement of parameters such as directivity,gain,and radiation power of the new metamaterial-based helix antenna.Therefore,the combination of Z-structure with the helix antenna shows the best performance.     

Using mobile node speed changes for movement direction change prediction in a realistic category of mobility models

In order to evaluate performance of protocols for ad hoc networks, the protocols have to be tested under realistic conditions. These conditions may include a reasonable transmission range, a limited buffer size, and realistic movement of mobile users (mobility models). In this paper, we propose a new and realistic type of random mobility models in which the mobile node has to decelerate to reach the point of direction change and accelerates with a defined acceleration to reach its intended speed. This realistic mobility model is proposed based on random mobility models. In reality, mobile objects tend to change their speed when they are going to change their direction, i.e. decelerate when approaching a direction change point and accelerate when they start their movement in a new direction. Therefore, in this paper, we implement this behavior in random mobility models which lack such specification. In fact, this paper represents our effort to use this accelerated movement to anticipate a probable direction change of a mobile node with reasonable confidence. The simulation type of this paper is based on traces produced by a mobility trace generator tool. We use a data mining concept called association rule mining to find any possible correlations between accelerated movement of mobile node and the probability that mobile node wants to change its direction. We calculate confidence and lift parameters for this matter, and simulate this mobility model based on random mobility models. These simulations show a meaningful correlation between occurrence of an accelerated movement and event of mobile node's direction change.     

Dam break flood wave under different reservoir’s capacities and lengths

Dam failure has been the subject of many hydraulic engineering studies due to its complicated physics with many uncertainties involved and the potential to cause many losses of lives and economical losses. A primary source of uncertainties in many dam failure analyses refers to prediction of the reservoir’s outflow hydrograph, which is studied in the present investigation. This paper presents an experimental study on instantaneous dam failure flood under different reservoir’s capacities and lengths in which the side slopes change within a range of 30°–90°. Thus, several outflow hydrographs are calculated and compared. The results reveal the role of the side slopes on dam break flood wave, such that lower side slope creates more catastrophic outflow. The reservoir capacity and length are also recognized to be important factors, such that they do affect peak discharge and time to peak of the outflow hydrograph. Finally, the paper presents two simple relations for peak discharge and maximum water level estimation at any downstream location.     

Application of artificial neural networks for prediction of coercivity of highly ordered cobalt nanowires synthesized by pulse electrodeposition

This study aims to predict the coercivity of cobalt nanowires fabricated by Alternating Current (AC) pulse. Coercivity is one of the most important properties of magnetic materials and its value shows the needed magnetic field in a way that magnetization of system is decreased to zero. There are many parameters such as pH of solution, oxidative and reductive times, oxidative and reductive voltages, interval between pulses (off-time), and concentration of deposition solution that have direct effect on materials magnetic properties of. Change of initial conditions to obtain the best results is very time consuming, therefore employing a method which can save both the time and cost is necessary. Hence, it this study Artificial Neural Network (ANN), which has numerous applications and has attracted many attentions in various fields, was applied. Through this study, an ANN was designed to present a template that is capable for predicting output data (coercivity) according to input data (pH, oxidative and reductive times, oxidative and reductive voltages, and off-time). Besides, in this research, the results for pH = 4 and 6 were investigated and the effect of off-time as well as the deposition time on coercivity were studied.     

INFLUENCE OF VIBRATION ON SORET-DRIVEN CONVECTION IN POROUS MEDIA

Two-dimensional thermosolutal natural convection with Soret effect under the simultaneous action of vibrational and gravitational accelerations is investigated. We consider a porous cavity saturated by a binary mixture and adopt the time-averaging formulation. For an infinite horizontal layer, a stability analysis is performed from which the threshold of stability is determined. Numerical simulations, using a pseudo-spectral Chebyshev collocation method, are performed to describe the convective motion. The problem is investigated for different aspect ratios with various directions of vibration. It is concluded that, for both the stationary and the Hopf bifurcation, the vertical vibration has a stabilizing effect while the horizontal vibration has a destabilizing effect on the onset of convection.     

Modeling the oxidative coupling of methane using artificial neural network and optimizing of its operational conditions using genetic algorithm

The effect of some operating conditions such as temperature, gas hourly space velocity (GHSV), CH₄/O₂ ratio and diluents gas (mol% N₂) on ethylene production by oxidative coupling of methane (OCM) in a fixed bed reactor at atmospheric pressure was studied over Mn/Na₂WO₄/SiO₂ catalyst. Based on the properties of neural networks, an artificial neural network was used for model developing from experimental data. To prevent network complexity and effective data input to the network, principal component analysis method was used and the number of output parameters was reduced from 4 to 2. A feed-forward back-propagation network was used for simulating the relations between process operating conditions and those aspects of catalytic performance including conversion of methane, C₂ products selectivity, C2 yielding and C₂H₄/C₂H₆ ratio. Levenberg-Marquardt method is presented to train the network. For the first output, an optimum network with 4-9-1 topology and for the second output, an optimum network with 4-6-1 topology was prepared. After simulating the process as well as using ANNs, the operating conditions were optimized and a genetic algorithm based on maximum yield of C₂ was used. The average error in comparing the experimental and simulated values for methane conversion, C₂ products selectivity, yield of C₂ and C₂H₄/C₂H₆ ratio, was estimated as 2.73%, 10.66%, 5.48% and 10.28%, respectively.     

Nanofiltration membranes for ionic liquid recovery

Nanofiltration membranes have been developed by interfacial polymerization using base PES ultrafiltration membranes. By varying the concentration of the reactive monomers present as well as the reaction conditions, the structure of the polymerized barrier layer has been modified. Here, the ability to concentrate low molecular weight sugars while allowing dissolved ionic liquids in aqueous solution to be recovered in the permeate has been investigated for application in biomass hydrolysis. The results obtained here indicate that the selectivity for 1-butyl-3-methylimidazoliumchloride (BmimCl) over glucose can be as high as 36.6. The membrane permeance was 2.31 L m^?2 h^?1 bar^?1.     

Integration of beamforming and uncertainty-of-observation techniques for robust ASR in multi-source environments

This paper presents a new approach for increasing the robustness of multi-channel automatic speech recognition in noisy and reverberant multi-source environments. The proposed method uses uncertainty propagation techniques to dynamically compensate the speech features and the acoustic models for the observation uncertainty determined at the beamforming stage. We present and analyze two methods that allow integrating classical multi-channel signal processing approaches like delay and sum beamformers or Zelinski-type Wiener filters, with uncertainty-of-observation techniques like uncertainty decoding or modified imputation. An analysis of the results on the PASCAL-CHiME task shows that this approach consistently outperforms conventional beamformers with a minimal increase in computational complexity. The use of dynamic compensation based on observation uncertainty also outperforms conventional static adaptation with no need of adaptation data.     

Modelling and evaluation of building integrated SOFC systems

This study presents the final results of a series of modelling steps which are undertaken for the performance assessment of the building cogeneration and polygeneration systems using solid oxide fuel cell (SOFC). Based on earlier work, generic SOFC cell stack and system models were developed and employed to analyze different SOFC systems configurations for optimal efficiencies, this SOFC system model is used to derive performance input data for transient whole-building and energy system simulation tools which contain simpler SOFC system models. These steps are shortly summarized here. Then the final step, the evaluation of building integrated co- and polygeneration SOFC systems in terms of primary energy demand and CO₂ emissions, employing such tools, is presented here for a polygeneration system with typical heating and cooling loads, and electricity demand profiles, for different SOFC systems, including a comparison to current standard technologies.