A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

Evaluation of Antioxidant and Antimicrobial Activities of Essential Oils from Carum copticum Seed and Ferula assafoetida Latex

Carum copticum and Ferula assafoetida have several medicinal properties including antispasmodic, carminative, sedative, analgesic, and antiseptic. Reactive oxygen species (ROS), reactive nitrogen species (RNS), hydrogen peroxide (H₂O₂), and thiobarbituric acid reactive substances (TBARS) scavenging activities of Carum and Ferula oils along with their antibacterial and antifungal activities were examined. Thymol (40.25%), γ‐terpinene (38.7%) and p‐cymene (15.8%) were detected as the main components of Carum oil while, β‐pinene (47.1%), α‐pinene (21.36%), and 1, 2‐dithiolane (18.6%) were the main components of Ferula oil. Inhibitory concentrations (IC50) for total radical scavenging were between 40 and 60 and 130 and 160 μg/mL of Carum and Ferula oil, respectively. Minimal inhibitory concentration (MIC) for Salmonella typhi, Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Aspergillus niger, and Candida albicans were 78 ± 8, 65 ± 7, 14 ± 3, 5 ± 2, 5.6 ± 1.3, and 8.8 ± 2.2 μg/mL of Carum oil, respectively. MIC for S. typhi, E. coli, S. aureus, B. subtilis, A. niger, and C. albicans were >200, >200, 125 ± 17, 80 ± 12, 85 ± 5, and 90 ± 11 μg/mL of Ferula oil, respectively. Accordingly, Carum and Ferula oils could be used as safe and effective natural antioxidants to improve the oxidative stability of fatty foods during storage and to preserve foods against food burn pathogens. Practical Application : This study clearly demonstrates the potential of Carum and Ferula oil especially Carum oil as natural antioxidant and antimicrobial agent. The chemical composition of essential oils was identified. Thus, identification of such compounds also helps to discover of new antioxidant, antibacterial and antifungal agents for potential applications in food safety and food preservation.     

Service reliability of offshore wind turbines

A probabilistic formulation is proposed to assess the performance of the support structure of offshore wind turbines based on their probability and expected time of exceeding specified drift thresholds. To this end, novel probabilistic models are developed to predict the mean and standard deviation of the drift ratio response of wind turbine support structures operating under day-to-day loads as a function of the wind turbine geometry and material properties, and loading conditions. The proposed models are assessed using a database of virtual experiments generated using detailed three-dimensional (3D) nonlinear finite element (FE) models of a set of representative wind turbine configurations. The developed models are then used in a random vibration formulation to estimate the probability and expected time of exceeding specified drift thresholds. As an example, the probability and expected time of exceeding specified drift thresholds are estimated for a typical offshore wind turbine at different wind speeds. A comparison is made between the results obtained based on the proposed models, those obtained using simulators commonly used in practice and detailed 3D nonlinear FE analyses.     

A new reactor concept for combining oxidative coupling and steam re‐forming of methane: modeling and analysis

A new and very promising application of auto‐thermal reactors is the coupling of endothermic and exothermic reactions where the product of the endothermic reaction is the desired one. Therefore, in this work, a reactor in which oxidative coupling of methane (OCM) and steam re‐forming of methane (SRM) reactions take place simultaneously was modeled. The results were obtained in a wide range of different conditions such as inlet feed, inlet temperature, portions of OCM and SRM catalysts, and inlet velocity. In selection of the catalysts, more attention was drawn to prevent re‐forming of OCM products. The main parameters of each reaction under different conditions such as conversion of the feed components, products selectivity and yield, temperature in the length of reactor, and component's concentration in the reactor were considered in course of this study. The results revealed that simultaneous OCM and SRM reactions in one reactor will tend to be auto‐thermal, and the waste of energy will be reduced. The results also show that complete conversion of water and majority of methane and oxygen will decrease the amount of unwanted products at the reactor's discharge–a constraint that exists in single reactors of each reaction specially OCM. Copyright © 2011 John Wiley & Sons, Ltd.     

The influence of depth of cut on the machinability of an alloyed austempered ductile iron

The volume fraction of high carbon austenite present in the microstructure of austempered ductile iron (ADI) is one of the important factors that influence the mechanical and physical properties of the alloy. Formation of martensite by TRIP (transformation induced plasticity) mechanism during the machining operation in which a large amount of stress is applied to the microstructure results in a decrease in machinability of austempered ductile iron which has affected the expansion of ADI in industry. In this article, the effect of depth of cut as a machining variable is assessed in an alloyed austempered ductile iron containing Cu, Ni and Mo. The measurements of mechanical properties including impact energy, tensile strength, hardness and microhardness along the cross-section of samples are reported for samples austenitized at 870 °C followed by austempering at 375, 340 and 300 °C. Results indicate that contrary to the behavior of many alloys, in austempered ductile iron, reducing the depth of cut will not improve the machinability. In the case of studied composition, cutting with depths of 0.5 and 0.1 mm had the best and worst results, respectively.     

Tuning parallel applications in parallel

In this paper, we present and evaluate a parallel algorithm for parameter tuning of parallel applications. We discuss the impact of performance variability on the accuracy and efficiency of the optimization algorithm and propose a strategy to minimize the impact of this variability. We evaluate our algorithm within the Active Harmony system, an automated online/offline tuning framework. We study its performance on three benchmark codes: PSTSWM, HPL and POP. Compared to the Nelder–Mead algorithm, our algorithm finds better configurations up to seven times faster. For POP, we were able to improve the performance of a production sized run by 59%.     

Effect of Cu2+ Ions and Buffering Capacity on Smectite Microstructure and Performance

Smectite is usually used as buffer clay for contaminant of high level nuclear waste canisters. Corrosion of the canisters will expose the buffer clay to Cu2+ ions as one of the corrosion products. This study investigates the effect of Cu2+ cations in a smectite, with and without addition of sodium carbonate in the clay, on its consolidation behavior and transmission characteristics. Characterization experiments conducted in the study included determination of changes in the buffering capacity and permeability properties of the clay in relation to the presence of varying concentrations of Cu2+, and consolidation experiments. Double-layer swelling forces and buffering capacity are seen to be dominant factors in the performance of the clays—apparently through their influence on formation and restructuring of microstructures in the overall smectite clay mixtures.     

Parameter identification of deep-bar induction motors using genetic algorithm

In recent years, the use of three-phase deep-bar induction motors in power systems has increased. Proper modeling and precise parameter identification of the model are essential for motors’ operating analysis. In this paper, among the proposed models of deep-bar induction motors, a model based on two-axis theory is discussed and developed to improve precision. A real coded genetic algorithm estimates the parameters of the model. The accuracy and validity of the model and its identified parameters are verified with the help of a 5.5 kW, 380 V, 50 Hz, 1,450 rpm deep-bar induction motor.     

A Single Input-Multiple Output Time Reversal UWB Communication System

Time reversal is a promising technique for the improvement of UWB communication systems. Intersymbol interference (ISI) limits the system performance in such wireless systems. This paper presents a general ISI analysis for time reversal UWB communication systems. The time reversal UWB system gives good performance for rates below the coherence bandwidth but at higher data rates the performance of the system is limited by intersymbol interference and bit error rate saturates even for high signal-to-noise ratio. To mitigate the ISI effects, a single input/multiple output (SIMO) time reversal UWB system is used and its performance is analyzed. It is shown that by using a SIMO TR transceiver, ISI reduces and the system capacity increases. Transmitted signal power at SIMO time reversal decreases, therefore in low data rate SISO performance is better than SIMO, But in high rate scenario, SIMO TR suppresses the ISI better than the SISO TR and its performance is better than SISO TR. It is possible to compensate the reduced power by using a receiver with more sensitivity.     

Control of three phase PWM rectifier using virtual flux‐based predictive direct power control and SVM under harmonic conditions

In this paper, a new predictive direct power control algorithm to control the PWM rectifier based on virtual flux (VF) is presented. In this algorithm, supply network and the line inductances are assumed as an induction machine and so virtual flux space vectors are assumed corresponding with the space vector of the network voltages. Instantaneous active and reactive powers and finally convertor average voltage in both stationary and rotating reference frames are calculated by the virtual flux space vector components. The main advantages of the proposed method are low total harmonic distortion of the input current and low ripple in the instantaneous active and reactive powers and direct current‐bus voltage under harmonic distorted condition of the supply voltage in comparison with voltage‐based predictive direct power control (V‐PDPC) method. Proposed VF‐PDPC method with space vector modulation switching strategy was tested in simulations and compared with the V‐PDPC method. Copyright © 2015 John Wiley & Sons, Ltd.