A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

The research dealt with the topic ' the aesthetics of design shape of interior spaces for the syndicate of physicians' as it reflects visions evolving to the level of tasting and positive interpretation for the space of work to be on a high design level.The research consisting of four chapters as follow; The first chapter examined the problem of the research contracted in the following question: Have the design shapes any role in achieving and showing the aesthetic side for the syndicate of physicians? so the goal of the research was showing the aesthetics of design shape of interior spaces for the syndicate of physicians, The chapter also included the objective spatial and temporal limits of research .Finally the terms were specified. T

Chemical spray pyrolysis technique was used at substrate temperature 250 ˚C with annealing temperature at 400 ˚C (for 1hour) to deposition tungsten oxide thin film with different doping concentration of Au nanoparticle (0, 10, 20, 30 and 40)% wt. on glass substrate with thickness about 100 nm. The structural, optical properties were investigated. The X-ray diffraction shows that the films at substrate temperature (250 ˚C) was amorphous while at annealing temperature have a polycrystalline structure with the preferred orientation of (200), all the samples have a hexagonal structure for WO3 and Au gold nanoparticles have a cubic structure. Atomic force microscopy (AFM) was used to characterize the morphology of the films. The optical pr

AgInSe2 (AIS) thin films solar cell involving of n-type AgInSe2 and Si of p-type substrate by using thermal evaporation method. The influence of annealing of the preparation AgInSe2 were considered to find the best properties of solar device. Thin film AIS have been deposited under the vacuum of 1.5*10-6 Torr with (400) nm thickness at R.T and annealing temperatures (473,573) K. Polycrystalline tetragonal structure for AIS thin films from XRD and increasing of surface roughness from AFM, energy gap values decreasing with increasing annealing temperatures, all films were negative type, I-V characteristics show increasing of efficiency with increasing of annealing temperatures.

PVA:PEG/MnCl2 composites have been prepared by adding (MnCl2) to the mixture of the poly vinyl alcohol (PVA) and poly ethylene glycol (PEG) with different weight percentages (0, 2, 4, 6, 8 and 10) wt.% by using casting method. The type of charge carriers, concentration (nH) and Hall mobility (μH) have been estimated from Hall measurements and show that the films of all concentration have a negative Hall coefficient. In D.C measurement increase temperature leads to decrease the electrical resistance. The D.C conductivity of the composites increases with the increasing of the concentration of additive particles and temperature. The activation energy decreases for all composites with increasing the concentration of the additive particles.

The synthesized ligand (3-(2-amino-5-(3,4,5-tri-methoxybenzyl)pyrimidin-4-ylamino)-5,5-dimethylcyclohex-2-enone] [H1L1] was characterized via fourier transform infrared spectroscopy (FTIR), 1H, 13C – NMR, Mass spectra, (CHN analysis), UV-vis spectroscopic approaches. Analytical and spectroscopic techniques like chloride content, micro-analysis, magnetic susceptibility UV-visible, conductance, and FTIR spectra were used to identify mixed ligand complexes. Its (ML13ph) mixed ligand complexes [M= Co (II), Ni (II), Cu (II), Zn (II), and Cd (II); (H1L1) = β-enaminone ligand=L1 and (3ph) =3-aminophenol= L2]. The results demonstrate that the complexes are produced with a molar ratio of M: L1:L2 (1:1:1). To generate the appropriate compl

A fluorescence microscopy considered as a powerful imaging tool in biology and medicine. In addition to useful signal obtained from fluorescence microscopy, there are some defects in its images such as random variation in brightness, noise that caused by photon detection and some background pixels in the acquired fluorescence microscopic images appear wrongly auto-fluorescence property. All these practical limitations have a negative impact on the correct vision and analysis of the fluorescent microscope users. Our research enters the field of automation of image processing and image analysis using image processing techniques and applying this processing and analysis on one of the very important experiments in biology science. This research

Abstract:

                The aim of this research to try to determine the type of expected relationship between inflation as the explanatory variable and market performance as a dependent variable, for that used data issued and published by the Central Bank of Iraq and the Iraqi Stock Exchange for a sample consisting of (159) observations using the intentional or intentional sampling method for the period extending between the months (January 2010 to March 2023), in the light of each of the Consumer Price Index (CPI), the Iraqi Stock Exchange Index, the number of traded shares and the number of market capital shares to ex

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve