In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

In order to improve the effectiveness, increase the life cycle, and avoid the blade structural failure of wind turbines, the blades need to be perfectly designed. Knowing the flow angle and the geometric characteristics of the blade is necessary to calculate the values of the induction factors (axial and tangential), which are the basis of the Blade Element Momentum theory (BEM). The aforementioned equations form an implicit and nonlinear system. Consequently, a straightforward iterative solution process can be used to solve this problem. A theoretical study of the aerodynamic performance of a horizontal-axis wind turbine blade was introduced using the BEM. The main objective of the current work is to examine the wind turbine blade’s perf

     Atenolol was used with ammonium molybdate to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between atenolol and ammonium molybdate in an aqueous medium to obtain a dark brown precipitate. Optimum parameters was studied to increase the sensitivity for developed method. A linear range for calibration graph was 0.1-3.5 mmol/L for cell A and 0.3-3.5 mmol/L for cell B, and LOD 133.1680 ng/100 µL and 532.6720 ng/100 µL for cell A and cell B respectively with correlation coefficient (r) 0.9910 for cell A and 0.9901 for cell B, RSD% was lower than 1%, (n=8) for the determination of ate

Twitter is becoming an increasingly popular platform used by financial analysts to monitor and forecast financial markets. In this paper we investigate the impact of the sentiments expressed in Twitter on the subsequent market movement, specifically the bitcoin exchange rate. This study is divided into two phases, the first phase is sentiment analysis, and the second phase is correlation and regression. We analyzed tweets associated with the Bitcoin in order to determine if the user’s sentiment contained within those tweets reflects the exchange rate of the currency. The sentiment of users over a 2-month period is classified as having a positive or negative sentiment of the digital currency using the proposed CNN-LSTM

In this article, the solvability of some proposal types of the multi-fractional integro-partial differential system has been discussed in details by using the concept of abstract Cauchy problem and certain semigroup operators and some necessary and sufficient conditions. 

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

This paper introduces a Laplace-based modeling approach for the study of transient converter-grid interactions. The proposed approach is based on the development of two-port admittance models of converters and other components, combined with the use of numerical Laplace transforms. The application of a frequency domain method is aimed at the accurate and straightforward computation of transient system responses while preserving the wideband frequency characteristics of power components, such as those due to the use of high frequency semiconductive switches, electromagnetic interaction between inductive and capacitive components, as well as wave propagation and frequency dependence in transmission systems.

Solar collectors, in general, are utilized to convert the solar energy into heat energy, where it is employed to generate electricity. The non-concentrating solar collector with a circular shape was adopted in the present study. Ambient air is heated under a translucent roof where buoyant air is drawn from outside periphery towards the collector center (tower base). The present study is aimed to predict and visualize the thermal-hydrodynamic behavior for airflow under inclined roof of the solar air collector, SAC. Three-dimensional of the SAC model using the re-normalization group, RNG, k−ε turbulence viscus model is simulated. The simulation was carried out by using ANSYS-FLUENT 14.5. The simulation