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The Intelligent Auto-Tuning Controller Design Based on Dolphin Echo Location for Blood Glucose Monitoring System
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This paper presents an enhancement technique for tracking and regulating the blood glucose level for diabetic patients using an intelligent auto-tuning Proportional-Integral-Derivative PID controller. The proposed controller aims to generate the best insulin control action responsible for regulating the blood glucose level precisely, accurately, and quickly. The tuning control algorithm used the Dolphin Echolocation Optimization (DEO) algorithm for obtaining the near-optimal PID controller parameters with a proposed time domain specification performance index. The MATLAB simulation results for three different patients showed that the effectiveness and the robustness of the proposed control algorithm in terms of fast generating insulin control action and tracking the dynamics behavior of the blood glucose level of the diabetic patients through minimizing overshoot, rise time and settling time in the transient state as well as the steady-state blood glucose level error is reduced approximately to zero and keep it in the desired glucose level, especially when we added a meal as disturbance effect.

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Attitude and Altitude Control of Quadrotor Carrying a Suspended Payload using Genetic Algorithm
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The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slun

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Predictive Value of Spectral Waveform Indices; Intimal Medial Thickness and Lumen Diameter of Carotid Artery in Iraqi Diabetic and Hypertensive Patients
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Background: Diabetes and hypertension are related to cardiovascular risk factors and are possible to detect development of atherosclerosis in cardiovascular system, were can predict their effect and measurement by ultrasound and Doppler study. These risk factors included increased intima-media thickness, resistive index (RI) and pulsatility index (PI) of the right common carotid arteries. Method: We studied 20 patients with diabetes and hypertension, and 20 patients with diabetes only, were examine right carotid arteries for these two groups. In this sample we studied the Lumen diameter of the Rt. carotid arteries, Intima – media thickness (IMT), peak systolic velocity, end diastolic velocity, and Pulsatility index, Resistance index were

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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Hematological Study of Infants Amoebiasis in Duhok City
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Out of 180 children, 60 (33.3%) have Amoebiasis infection as diagnosed by direct wet smear and Saturated Salt Solution (SSS). SSS method is more significant (P=0.001) in diagnosis of the disease. Number of children infected with Amoebiasis infection is higher in infants aged 1-6 months, but without any significant difference to ages 6-12 or 12-18 months. In contrast, infants aged 18-24 months are significantly differant (P=0.01) as the infection rate is 16.6%. Gender also is seen to be reduced in significance (P= 0.001) for females aged 18-24 months. Blood profile of the involved infants has shown a significant variation (P=0. 01) for all blood profile parameters (RBC (P=0.05), WBC (P=0.001), Lymphocytes (P=0.05), Granulated WBC (P=0.05),

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Human β-Defensin 2 as a Novel Diagnostic Marker of Iraqi Patients with Rheumatoid Arthritis
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Rheumatoid arthritis (RA) is an autoimmune disorder of the joints that is characterized by extra-articular involvement in addition to inflammatory arthritis. Joint and periarticular tissue loss brought on by inflammation results in functional impairment. To lessen the significant daily challenges that patients confront and to ensure better outcomes, early detection and treatment are essential. The study's objective was to establish the use of human β-defensin-2 (HBD-2) as a RA diagnostic marker. A total of 60 RA patients and 30 healthy controls participated in the research. The ELISA technique was used to measure serum HBD-2. The following tests were performed: complete blood count (CBC), erythrocyte sedimentation rate (ESR), renal func

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Power-Efficient Virtual Machine Placement in Cloud Datacenters using Heuristic Assisted Enhanced Discrete Particle Swarm Optimization
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    The increase in cloud computing services and the large-scale construction of data centers led to excessive power consumption. Datacenters contain a large number of servers where the major power consumption takes place. An efficient virtual machine placement algorithm is substantial to attain energy consumption minimization and improve resource utilization through reducing the number of operating servers. In this paper, an enhanced discrete particle swarm optimization (EDPSO) is proposed. The enhancement of the discrete PSO algorithm is achieved through modifying the velocity update equation to bound the resultant particles and ensuring feasibility. Furthermore, EDPSO is assisted by two heuristic algorithms random first fit (RFF) a

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Optimal characteristics of wind turbine to maximize capacity factor
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The capacity factor is the main factor in assessing the efficiency of wind Turbine. This paper presents a procedure to find the optimal wind turbine for five different locations in Iraq based on finding the highest capacity factor of wind turbine for different locations. The wind data for twelve successive years (2009-2020) of five locations in Iraq are collected and analyzed. The longitudes and latitudes of the candidate sites are (44.3661o E, 33.3152o N), (47.7738o E, 30.5258o N), (45.8160o E, 32.5165o N), (44.33265o E, 32.0107o N) and (46.25691o E, 31.0510o N) for Baghdad, Basrah, Al-Kut, Al-Najaf, and Al-Nasiriyah respectively. The average wind velocity, standard deviation, Weibull shape and scale factors, and probability density functi

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Effect of laser process an inclined surface cutting of mild steel then analysis data statistically by RSM
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The regression analysis process is used to study and predicate the surface response by using the design of experiment (DOE) as well as roughness calculation through developing a mathematical model. In this study; response surface methodology and the particular solution technique are used. Design of experiment used a series of the structured statistical analytic approach to investigate the relationship between some parameters and their responses. Surface roughness is one of the important parameters which play an important role. Also, its found that the cutting speed can result in small effects on surface roughness. This work is focusing on all considerations to make interaction between the parameters (position of influenc

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Optimized Artificial Neural network models to time series
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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Optimization of Lovastatin Production from A Local Isolate of Aspergillus terreus A50 in Solid State Fermentation by Classical and Statistical Methods
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Lovastatin is one of the most important compounds that is produced from some filamentous fungi, being employed in the reduction of hypocholesterolemia. The results of screening, after the collection of seventy-three local fungal isolates from different areas, demonstrated that the local isolate Aspergillus terreus A50 was the best isolate for lovastatin production, with a concentration of 12.66 µg/ml, through the submerged fermentation. Lovastatin produced from A. terreus A50 showed antimicrobial activities against a Candida albicans isolate. Solid state fermentation (SSF) was the best system to produce the highest yield of lovastatin by A. terreus A50 as compared to the submerged fermentation (SmF)

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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