Consecutive charging and discharging of a PCM-based plate heat exchanger with zigzag configuration
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
The settlement evaluation for the jet grouted columns (JGC) in soft soils is a problematic matter, because it is influenced by the number of aspects such as soil type, effect mixture between soil and grouting materials, nozzle energy, jet grouting, water flow rate, rotation and lifting speed. Most methods of design the jet-grouting column based on experience. In this study, a prototype single and group jet grouting models (single, 1*2, and 2*2) with the total length and diameter were (2000 and 150 mm) respectively and clear spacing (3D) has been constructed in soft clay and subjected to vertical axial loads. Furthermore, different theoretical methods have been used for the estimation
A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro
... Show MoreBackground: Myasthenia gravis is an autoimmune disease of the neuromuscular junction that results in fluctuating muscle weakness as well as significant fatigue. Disease exacerbation is a critical condition, and the predisposing factors for it need to be identified to improve preventive measures.
Objectives: Our study aims to determine the predisposing factors for myasthenia gravis exacerbations in a group of Iraqi patients.
Subjects and Methods: A total number of 30 myasthenia gravis patients were admitted to the hospital with an exacerbation of their symptoms, determined as the development of functional disability, dysphagia, or respiratory fai
... Show MoreThis paper performance for preparation and identification of six new complexes of a number of transition metals Cr (lII), Mn (I1), Fe (l), Co (II), Ni (I1), Cu (Il) with: N - (3,4,5-Trimethoxy phenyl-N - benzoyl Thiourea (TMPBT) as a bidentet ligand. The prepared complexes have been characterized, identified on the basis of elemental analysis (C.H.N), atomic absorption, molar conductivity, molar-ratio ,pH effect study, I. Rand UV spectra studies. The complexes have the structural formula ML2X3 for Cr (III), Fe (III), and ML2X2 for Mn (II), Ni (II), and MLX2 for Co (Il) , Cu (Il).
The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for