This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

Summary Kidney transplantation is widely performed nowadays as an optimal treatment of end stage kidney diseases. Complications such as stenosis in graft renal arteries anastomosis may occur. Different suturing techniques are available for renal artery anastomosis. We aimed to compare the incidence of renal artery stenosis of the transplanted kidney when two suture techniques (continuous or interrupted) used for renal artery anastomosis. Therefore, a retrospectively comparative study was conducted on 44 patients managed with kidney transplantation during the years 2009-2011. Patients assigned into two groups; first group included 20 patients namely, continuous suture group, and the second group included 24 patients in whom the allograft art

The waste sorting and recycling plant in the district of al- Mahmudiya (Yusufiya) is the only laboratory in Baghdad governorate. It is the only one in Iraq that collects and recycles waste. After sorting, we have packages of raw materials (aluminum cans, glass bottles, plastic bottles, Nylon bags) as well as natural fertilizers (food residues and others) and a sanitary landfill with specifications that meet international standards; However, the absence of a structure for the management of the plant (manager, assistant manager, accountant, etc.) in addition to the non-supply of waste on a daily and continuous basis and the lack of cooperation of the Municipality of Baghdad with the management of the plant led to delay in the work

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

n this paper, we formulate three mathematical models using spline functions, such as linear, quadratic and cubic functions to approximate the mathematical model for incoming water to some dams. We will implement this model on dams of both rivers; dams on the Tigris are Mosul and Amara while dams on the Euphrates are Hadetha and Al-Hindya.

One of the main parts in hydraulic system is directional control valve, which is needed in order to operate hydraulic actuator. Practically, a conventional directional control valve has complex construction and moving parts, such as spool. Alternatively, a proposed Magneto-rheological (MR) directional control valve can offer a better solution without any moving parts by means of MR fluid. MR fluid consists of stable suspension of micro-sized magnetic particles dispersed in carrier medium like hydrocarbon oil. The main objectives of this present research are to design a MR directional control valve using MR fluid, to analyse its magnetic circuit using FEMM software, and to study and simulate the performance of this valve. In this research, a