This research  describes the design & implementation of frequency synthesizer using single loop Phase lock loop with the following specifications: Frequency range (1.5 – 2.75) GHz,Step size (1 MHz), Switching time 36.4 µs, & phase noise @10 kHz = -92dBc & spurious -100 dBc

  The development in I.C. technology provide the simplicity in the design of frequency synthesizer because it implements the phase frequency detector(PFD) , prescalar &  reference divider in single chip. Therefore our system consists of  a single chip contains (low phase noise PFD, charge pump, prescalar  & reference divider), voltage controlled oscillator , loop filter & reference oscillator. The single chip

Anti-Neutrophil Cytoplasmic Antibodies (ANCA) are a heterogeneous group of autoantibodies with a broad spectrum of clinically associated diseases. The diagnostic value is established for Proteinase 3 (PR3)-ANCA as well as Myeloperoxidase (MPO)-ANCA. To estimate the frequency of anti-neutrophile cytoplasmic antibodies (ANCA) in sera from a group of Iraqi patients with some autoimmune diseases compared with a healthy control group. Serum samples were collected from one hundred patient, 47 males and 53 females; with age range of 16-70 years; 20 specimens from patients with systemic lupus erythematosus (SLE), 30 from patients with ulcerative colitis (UC), and 50 from patients with rheumatoid arthritis (RA). A group of 40 apparently healthy b

The problem of frequency estimation of a single sinusoid observed in colored noise is addressed. Our estimator is based on the operation of the sinusoidal digital phase-locked loop (SDPLL) which carries the frequency information in its phase error after the noisy sinusoid has been acquired by the SDPLL. We show by computer simulations that this frequency estimator beats the Cramer-Rao bound (CRB) on the frequency error variance for moderate and high SNRs when the colored noise has a general low-pass filtered (LPF) characteristic, thereby outperforming, in terms of frequency error variance, several existing techniques some of which are, in addition, computationally demanding. Moreover, the present approach generalizes on existing work tha

Quadrotors are coming up as an attractive platform for unmanned aerial vehicle (UAV) research, due to the simplicity of their structure and maintenance, their ability to hover, and their vertical take-off and landing (VTOL) capability. With the vast advancements in small-size sensors, actuators, and processors, researchers are now focusing on developing mini UAV’s to be used in both research and commercial applications. This work presents a detailed mathematical nonlinear dynamic model of the quadrotor which is formulated using the Newton-Euler method. Although the quadrotor is a 6 DOF under-actuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is under-actuated. The der

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials.