Engineering and Technology Journal

Losses in the transmission line have a significant and growing impact on power systems around the world. Line losses overheat power lines, therefore electrical power systems require powerful processors and intelligent management methods. Flexible AC Transmission System (FACTS) device UPFC is one of the most important devices due to its ability to reduce total line losses that cause an increase in the transmission line capacity of the power system. In this paper, we used Particle Swarm Optimization (PSO) to determine the optimal location for the installation of UPFC device to minimize losses in the transmission line in the Iraqi international grid (ING) 400kV using a proportional-integral (PI) based UPFC controller. The potential solutions of PSO are called particles. All the particles selected in this controller depend on their parameter only, which keeps feasible solutions in their memory. The algorithm is coded in MATLAB and it is incorporated with the conventional Newton Raphson’s load flow analysis. The result shows that the proposed optimization method applied for two UPFC compensator parameters in the power system contributed to minimizing the active and reactive power losses under normal operating conditions using a modified version of the PSO algorithm

Photovoltaic generators (PVGs) are one of the most popular renewable energy sources (RESs), which achieve 47% of RES in microgrids. The aim of this work is to design and simulate a PVG system with a rated power of about 1,621 kW at the standard test conditions (STC), i.e., 1,000 W/m2 and 25ºC. The main components of the proposed PVG are 12 PV panels connected in series (the peak power of a PV panel at STC is about 135 W). A DC-DC boost converter is proposed for implementing the maximum power point tracking (MPPT) algorithm. The proposed MPPT algorithm is tested under extreme conditions; a wide range of change in temperature, irradiance, and load variations. The boost converter is designed to verify stable power flow from the PVG to the load. The calculated and the simulation results using MATLAB/Simulink are in good agreements and the maximum efficiency of the implemented MPPT algorithm is about 99%.

A huge traffic flow in the next generation network is anticipated due to the rising in number of users and the new services that need low end-to-end latency causing a large signaling load on the Core Network (CN). In order to mitigate this issue, many revolutionary architectures have been proposed to reduce this burden such as Cloud Radio Access Network (C-RAN). In this paper, a new C-RAN distributed core network architecture has been proposed by splitting some CN functions and grouping them into one location with Base Band Units (BBUs). As a measure of testing the proposed architectures and by using the MATLAB, the number of signaling messages processed by the control entities was analyzed. The evaluation results indicate a significant improvement if it have been compared to Long Term Evolution (LTE) architecture in terms of signaling load reduction, As the average signaling load was reduced by 46.04 percent in one of the proposed architectures when the number of user equipments increased.

In the VLSI circuits, power dissipation is a critical design parameter and it plays a vital role in the performance of different digital systems. The decrease in chip size along with the increase in chip density and complexity will increase the difficulty in designing higher performance and low power digital systems. Therefore, achieving a fast and low power system is the major concern of VLSI designers. Most of the digital systems have different math operations in their architectures. This paper focuses on the multiplication operation. Multiplication requires more iterations, long time, large area, and consumes high power of the digital system compared with the other basic computation operations. Hence to improve the system's performance, it is required to design a high speed and low power multiplier. In this paper, a dynamic power dissipation is targeted; therefore, different designs of multiplier algorithms such as a sequential multiplier, array multiplier, Booth’s multiplier (Radix-2), and modified Booth’s multiplier (Radix-4) are proposed to investigate the design that consumes the lowest dynamic power. New techniques such as VHDL and Basic Logic Elements are presented and applied to the proposed designs. The VHDL approach satisfies the highest optimization criteria in dynamic power at 87% for the sequential multiplier than the traditional ones.

or Orthogonal Frequency Division Multiplexing (OFDM) and other communication systems, many estimating approaches have been developed to estimate the channel state information and lower the Bit Error Rate (BER). These estimating methods, however, are still subject to the influence of large peak powers compared to average powers. Reduced computational complexity is one of the most significant factors to consider while developing a new estimate algorithm. This study aims to provide a novel design of the Packet-Discrete Wavelet Transform (P-DWT) algorithm for channel estimation in wireless OFDM instead of the fast Fourier transform (FFT). It is presented to retrieve the code of a spread spectrum signal and transmitted data bits, and it is compared to particle swarm optimization PSO and least mean square (LMS) optimization. The suggested approach reduces the computing cost of DWT by recognizing the Packet Wavelet Transform (PWT) coefficients and local points, findings utilizing P-DWT channels generated from both models and measurements show that the proposed technique outperforms pilot-based channel estimation in terms of bit error rate under sparseness conditions BER. Moreover, as compared to typical semi-blind approaches, the estimation accuracy is enhanced while computing cost is reduced.

Pain is considered as an emotional experience and a restless feeling associated with tissue damage. When the interpretation begins in the brain, the sensation of pain occurs; a signal transmitted to the brain through the nerve fiber. Pain helps the body to stop further damage to the tissues. Since there are numerous ways to convey and feel pain, the perception of pain is special to all. Technology that promotes pain assessment is an urgent need to reduce restless feelings and suffering. This paper aims to demonstrate the issues and challenges facing the patient’s pain assessment based on facial expression. The design and implementation of an automatic pain recognition system and explain the various concepts relevant to it, such as the type of modalities, the procedure of collection and processing data sequentially to reach the classifier. Then presenting clarification for various signals as input data (facial expressions, body movement, and vocalization). This survey would positively help researchers to supplement their efforts towards the expansion of patients' pain assessment based on facial expression.

This paper proposes a Multi Object Particle Swarm Optimization (MOPSO) to find the optimal location and capacity of Distributed Generation and D-STATCOM device. The objective function has adapted with a multi -objectives function to improve voltage profile, the voltage stability and reduce the total power loss of the Radial Distribution System (RDS). Basically, the voltage stability index (VSI) has been used to pre-determine the optimal location of DG and D-STATCOM. Then, a MOPSO applies to achieve the suitable size of DG and D-STATCOM units with different load models. The proposed method is compared with other existing methods and it was obtained losses reductions and enhancement voltage stability and average voltage when was tested on IEEE 33-bus and real Iraqi 65-bus radial distribution system through simulation using MATLAB. Furthermore, different cases were considered for using the (MOPSO) algorithm at different load factors

In this paper, crystalline optical fibers were used as a sensor for sensing the zinc ion concentration using the image processing technique. The image of the laser spot transmitted through the optical fiber crystal sensor for each concentration of zinc ion solution. The sensor was made by welding a piece of LMA-10 crystal optical fiber from both ends of a single-mode optical fiber to obtain an SM-PCF-SM type sensor. And it is possible to distinguish between one concentration and another by studying the change of the images obtained as a result of changing the concentration of the zinc ion. The sensitivity of the manufactured sensor was about 73.47%.

The most effective treatment for cataracts is to remove the cloudy crystalline natural lens and implant an intraocular lens (IOL) in its place. These refractive (IOL) provide the same focusing as do the natural lens. Two refractive IOLs are designed and analyzed in this paper—these IOL are made of (PMMA, and Acrylic). The quality of the retinal image is analyzed and compared with the healthy eye, which is based on the (Liou-Brennan) eye model) LBEM). Polychromatic Point Spread Function (PSF), Modulation Transfer Function (MTF), spot diagram, Encircled Energy (EE), and monochromatic aberration are used as acceptable criteria within the Zemax software.

Improve medical image visualization is a critical preliminary step before further imagery processing like analyzing texture, extracting features, and segmentation. Imagery noises in medical images are frequently occurred as a consequence of different artificial processes such as acquisition, sending and receiving, and storing & retrieving processes. As a result, the quality of image visualization is degraded. Therefore, a de-noise process is important in order to maintain good image quality for medical purposes. In this paper, medical image enhancement aims to de-noise as much as possible while maintaining detailed features and edges. This work employed an optimization algorithm called "Bat" to enhance the quality of the medical images and also compare it with other methods such as Gaussian filter, median filter, and bilateral and Wiener filter. Obtained image quality was evaluated using range of reference metrics, like, peak signal to noise ratio (PSNR), mean square error (MSE), structural similarity index measure (SSIM), and signal to noise ratio (SNR). Bat algorithm achieved the best PSNR, SNR, MSE, SSIM values compared to other filters. Findings presented in this research showed that the PSNR performance of the proposed method is (60.6, 55.6, 64.9, 63.6), MSE is (1.125, 1.43, 2.95, 1.15), Gaussian noise, salt-and-pepper noise, speckle noise, Poisson noise on order

Axial Flux Permanent Magnet Synchronous Motor (AFPMSM) are very attractive candidates for driving applications due to their high efficiency, high torque-to-weight ratio, high power density, small magnetic thickness, and simplicity of construction. On the other hand, AFPMSM produces undesirable torque ripple in the developed electromagnetic torque, affecting their output performance. An intelligent control method is proposed in this paper to reduce torque ripple and improve the dynamic performance of AFPMSM. The vector control, employing the Field Oriented Control (FOC) technique, was used to improve the dynamic performance of the AFPMSM. The speed and torque controllers are achieved using the decoupling method. The intelligent control was designed to improve the performance of AFPMSM obtained from PI-PSO. The Adaptive Neuro-Fuzzy Inference System (ANFIS) was used as an Intelligent controller to integrate both the speed and torque constraints in a single training procedure. Training data for ANFIS was obtained from PI-PSO with a multi-objective cost function that includes the torque ripple and speed response criteria. The approach gave great results in terms of speed performance in different
operating conditions and in tracking the required speed in load and no-load. In
addition, the torque ripple was reduced by 10.04% and 46.67% compared with
PI-PSO and Multi-objective cost function of speed, respectively

Human health is represented due to the measurement of vital signs. The basic vital signs are temperature, heart pulse rate, oxygen percentage in blood, blood pressure, etc. These signs are changes according to the physical and mental status of the individual. So measuring and monitoring those signs are very important. In this work, design and implementation of human Temperature Sensor are submitted. This is achieved using optical fiber technology. Two sensor diameters were tested; 125 μm and 60μm. The obtained results show a shifting in wavelength towards the red region due to temperature application. The submitted sensor has good sensitivity and linearity. Both sensors exhibit good responsivity, sensitivity, and high linearity. The sensitivity is increased about five times when the diameter is decreased

The emergence of COVID-19 disease in the world has moved the wheel of scientific research in order to detect it in the best method, and the fastest of these methods is the use of Artificial Intelligence (AI) techniques to help medical professionals detect COVID-19. The proposed topic is aim to develop algorithm based on combination between image processing techniques with artificial
intelligence to diagnose COVID-19. The proposed algorithm consists of five
stages to detect and classify COVID-19 from Computer Tomography (CT)
images. These stages include; The first of these stages is to collect data from
hospitals as real data and from Kaggle website for patients and healthy people,
then the stage before removing the noise and converting it from RGB to
grayscale, then we improve the image, segmentation and formalities, the other
stage is a stage used to extract the important characteristics, and the last stage is
the classification of images CT scan using Feed Forward Back Propagation
Network (FFBPN) and Support Vector Machine (SVM )and compare the result
between them and see if the person is infected or healthy. This study was
implemented in MATLAB software. The results showed that the noise
cancellation technology using anisotropic filtering gave the best results. As for
the optimization technology, only the brightness of the images has been
increased. At the stage of segmentation of the area of lung injection using the
area transplant method, the best results are detection of COVID-19 from other
healthy tissues. The FFBPN gave the best results for detecting and classifying
COVID-19 as well as determining whether a person has been infected or not. The
results of the proposed methodology in accurate and rapid detection of

This paper presents an algorithm to solve the unit commitment problem using the intelligence technique based on improved Particle Swarm Optimization (IPSO) for establishing the optimal scheduling of the generating units in the electric power system with the lowest production cost during a specified time and subjected to all the constraints. The minimum production cost is calculated based on using the Lambda Iteration method. A conventional method was also used for solving the unit commitment problem using the Dynamic Programming method (DP). The two methods were tested on the 14-bus IEEE test system and the results of both methods were compared with each other and with other references. The comparison showed the effectiveness of the proposed method over other methods.

This paper proposes an integrated Economic Load Dispatch (ELD) and Automatic Generation Control (AGC) for interconnected power systems. Based on their participation factor determined from the economic load dispatch calculation, each unit shares the total change in the same control region. In this study, two control areas are considered. Three thermal units are located in each control area. An integral controller (I) is only used for the AGC mechanism's secondary controller and is used for the primary controller for the ELD mechanism. An Improved Grey Wolf Optimizer (IGWO) technique is used to evaluate the optimum parameters of the integral controllers for primary and secondary controllers. An integral time square error (ITSE) has been used as the objective function to tune the suitability of the proposed controller gains. The simulation results demonstrate that the integrated AGC with ELD has the superiority in reducing the overshoot and fast steady state compared with AGC only.