The research aims to a statement of specificity of the Controller of (academic achievement, specialty, job title, length of service, Gender) and its impact on performance, Through a proposed appraisal form includes three main axes and each axis including several specialized elements in the supervisory work in form (check list). as is the importance of research to enable officials of oversight bodies financial identify and diagnose performance Controller through what has this observer of the process of scientific properties when performing supervisory work. Be summarized problem of the research that the lack of regulatory institution with the Controller interesting in terms of the necessary characteristics and requirements and inv

In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.

The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

In this work, the relationship between the ionospheric parameters (Maximum Usable Frequency (MUF), Lowest Usable Frequency (LUF) and Optimum working Frequency (OWF)) has been studied for the ionosphere layer over the Iraqi zone. The capital Baghdad (44.42oE, 33.32oN) has been selected to represent the transmitter station and many other cities that spread over Iraqi region have represented as receiver stations. The REC533 communication model considered as one of the modern radio broadcasting version of ITU has been used to calculate the LUF parameter, while the MUF and OWF ionospheric parameters have been generated using ASAPS international communication model which represents one of the most advanced  and accurate HF sky wave prop

Background

Respiratory tract aspergillosis is a pulmonary disease cause by aspergillus species which are opportunistic fungi that mainly infect immuno-compromised patients .

 Objective(s)

The present study aimed to detect the frequency of pulmonary aspergillosis among clinically suspected and under follow up tuberculosis patients conducted at Tropical Diseases Teaching Hospital, Omdurman, Khartoum State , Sudan during the period from December 2019 to November 2020.

 Materials and Methods

One hundred and fifty sputum samples were collected from suspected cases of pulmonary tuberculosis and under follow up tuberculosis patients. All specimens were examined using 20% KOH and cultured on two

In this work, the relationship between the ionospheric parameters (Maximum Usable Frequency (MUF), Lowest Usable Frequency (LUF) and Optimum working Frequency (OWF)) has been studied for the ionosphere layer over the Iraqi zone. The capital Baghdad (44.42^oE, 33.32^oN) has been selected to represent the transmitter station and many other cities that spread over Iraqi region have represented as receiver stations. The REC533 communication model considered as one of the modern radio broadcasting version of ITU has been used to calculate the LUF parameter, while the MUF and OWF ionospheric parameters have been generated using ASAPS international communication model which represents one of the most advanced  and

Background: The study of human leukocytes (HLA) alleles, and haplotype frequencies within populations provide an important source of information for anthropological investigation, organ and hematopoietic stem cell transplantation as well as disease association, certain diseases showed association with specific alleles specially those of known or suspected hereditary origin or immunological basis, whether simple renal cyst is congenital or acquired is still unclear and need to be investigated.Objectives: To study the genetic aspect of simple renal cysts by detecting the gene frequency and the haplotype of HLA class I of patients with simple renal cysts, and to find the presence of these cysts in other family members.Method: Thirty patient

Three hundred and fifty five patients with hepatitis were investigated in this study all cases gave negative result with HBs Ag , IgM-anti HCV , IgM-anti HEV, IgM-anti HDV and anti-HIV tests . The frequency of IgM-anti HAV was 113 and the percentage was 32 % in all ages but when these patients divided into five groups dependent on ages. The highest percentage of IgM-anti HAV was (45%) in age <10 and the percentage declined with age increase till to 9% in age >41 year.

ABSTRACT Background: According to Branemark’s protocol, the waiting period between tooth extraction and implant placement is 6–8 months; this is the late placement technique. Achieving and maintaining implant stability are prerequisites for a dental implant to be successful. Resonance Frequency Analysis (RFA) is a noninvasive diagnostic method that measures implant stability. The aim of this study was to investigate the influence of treatment protocol and implant dimensions on primary implant stability utilizing RFA. Materials and methods: This study included 63 Iraqi patients (37 male, 26 female; ranging 22-66 years). According to treatment protocol, the sample was divided into 2 groups; A (delayed) & B (immediate). Dental im

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