The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated online by a non-linear observer bandwidth, that is as a function of the observation errors. Moreover, with the help of disturbance estimation, a novel sliding manifold is constructed with parameters adaptively adjusted by a dynamic nonlinear bandwidth function to reduce the impact of high gain problems, especially noise-sensitivity. A continuous sliding-mode (CSM) based component is also designed to handle disturbance estimation errors. Third, the stability of the closed loop system, including the proposed controller and estimator, is mathematically proved using the Lyapunov theorem. Finally, the comparative simulation results show that the proposed method has superior robustness and temperature tracking performance.
Management of Foreign Exchange Rate Exposure by Using Financial Hedging An Analytical Empirical Study The main purpose of this Research is to investigate the ability to reduce the effect of exchange rate fluctuation on firm value , by usage appropriate hedging strategies to provide the firms force to adopted with complex and highly uncertainty conditions , characteristic of the most of the financial markets . The field of this study is the giant five Multinational on the world. Nokia, Toyota Motor, Intel , Coca Cola, Microsoft. practical analysis is provide the truth of all study's hypothesis , and it is reach to many of conclusion, the most important of them is Stem from unexpected fluctuation on nominal ex
... Show MoreThe gas chromatography (GC) method in analytical chemistry is a quick and accurate method to detect volatile components like ethanol. A method for determining volatile components known as Headspace chromatography (HS-GC) was developed along with an internal standard method (ISM) to identify ethanol in fermented broth in the laboratory. The aim of this research is determining the concentration of ethanol in fermented broth using capillary column (ZB-1). This method can analyze ethanol concentrations in the fermented medium broth ranging from 10 to 200 g/L. The validation of this method was done in order to obtain the results to be of high precision and the significant, precision was represented as the relative standard deviation (RSD) which
... Show MoreThis paper presents the ability to use cheap adsorbent (corn leaf) for the removal of Malachite Green (MG) dye from its aqueous solution. A batch mode was used to study several factors, dye concentration (50-150) ppm, adsorbent dosage (0.5-2.5) g/L, contact time (1-4) day, pH (2-10), and temperature (30-60) The results indicated that the removal efficiency increases with the increase of adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature. An SEM device characterized the adsorbent corn leaves. The adsorption's resulting data were in agreement with Freundlich isotherm according to the regression analysis, and the kinetics data followed pseudo-first-order kinetic with a correlation
... Show MoreThe current study examined the impact of using PowerPoint presentation on EFL student’s attendance, achievement and engagement. To achieve the aim of this study, three null hypotheses have been posed as follows: There is no statistically significant difference between the mean score of the experimental group attendance and that of the control one; there is no statistically significant difference between the mean score of the experimental group achievement and that of the control one, and there is no statistically significant difference between the mean score of the experimental group engagement and that of the control one. To verify a hypothesis, a sample of sixty students is chosen randomly from the third year, department of English,
... Show MoreThis study aims to assess the accuracy of digital elevation model (DEM) created with utilization of handheld Global Positioning System (GPS) and comparing with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. It is known that the quality of the DEM is affected by both of accuracy of elevation at each pixel (absolute accuracy) and accuracy of presented morphology (relative accuracy). The University of Baghdad, Al Jadriya campus was selected as a study area to create and analysis the resulting DEM. Additionally, Geographic Information System (GIS) was used to visualize, analyses and interpolate GPS track points (elevation data) of the study area. In this
... Show MoreSensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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