The peristaltic transport of power-law fluid in an elastic tapered tube with variable cross-section induced by dilating peristaltic wave is studied. The exact solution of the expression for axial velocity, radial velocity, stream function, local shear stress, volume of flow rate and pressure gradient are obtained under the assumption of long wavelength and low Reynolds number. The effects of all parameters that appear in the problem are analyzed through graphs. The results showed that the flux is sinusoidal in nature and it is an increasing function with the increase of whereas it is a decreasing function with the increase of . An opposite behavior for shear strain is noticed compared to pressure gradient. Finally, trapping p
... Show MoreSolar module operating temperature is the second major factor affects the performance of solar photovoltaic panels after the amount of solar radiation. This paper presents a performance comparison of mono-crystalline Silicon (mc-Si), poly-crystalline Silicon (pc-Si), amorphous Silicon (a-Si) and Cupper Indium Gallium di-selenide (CIGS) photovoltaic technologies under Climate Conditions of Baghdad city. Temperature influence on the solar modules electric output parameters was investigated experimentally and their temperature coefficients was calculated. These temperature coefficients are important for all systems design and sizing. The experimental results revealed that the pc-Si module showed a decrease in open circuit v
... Show MoreThe speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
In this paper, the 5 minutes measured wind speed data for year 2012 at 10 meter height for Tweitha have been statically analyzed to assess the time of wind turbine electrical power generation. After collection Tweitha wind data and calculation of mean wind speed the cumulative Weibull diagram and probability density function was ploted, then each of cumulative Weibull distribution, cut-in and furling turbine wind speed could be used as a mathematical input parameters in order to estimate the hours of electrical power generation for wind turbine during one day or one year. In Tweitha site, found that the average wind speed was (v= 1.76 m/s), so five different wind turbines were be selected to calculate hours of electrical generation for A
... Show MoreRecently a large number of extensive studies have amassed that describe the removal of dyes from water and wastewater using natural adsorbents and modified materials. Methyl orange dye is found in wastewater streams from various industries that include textiles, plastics, printing and paper among other sources. This article reviews methyl orange adsorption onto natural and modified materials. Despite many techniques available, adsorption stands out for efficient water and wastewater treatment for its ease of operation, flexibility and large-scale removal of colorants. It also has a significant potential for regeneration recovery and recycling of adsorbents in comparison to other water treatment methods. The adsorbents described herein were
... Show MoreThe advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages
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