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Performance Comparison of Different Advanced Control Schemes for Glucose Level Control under Disturbing Meal
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Abstract

In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controller. In spite that Min-max optimal controller gave better disturbance rejection capability than classical optimal controller, classical sliding mode controller could outperform Min-max controller. However, it has been shown that integral sliding mode controller is the best of all in terms of disturbance rejection capability.

 

Key words: Optimal LQR control, Optimalminimax control, Sliding mode control, Integral sliding mode control.

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Integration The Cost Techniques with Balanced Scorecard for The Purposes of Measuring and Evaluating Performance
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The effective application of the method of measuring and evaluating performance according to the Balanced  Scorecard the need for an information system a comprehensive and integrated for internal and external environment, Which requires the need to develop accounting information system in general and cost management information systems to suit the particular requirements of the environment in terms of the development of modern methods of measurement to include the use of some methods that have proven effective in measuring and evaluating performance.

The research problem in need of management to develop methods of measuring and evaluating performance through the use of both financial measures and non

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Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Fast lightweight encryption device based on LFSR technique for increasing the speed of LED performance
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LED is an ultra-lightweight block cipher that is mainly used in devices with limited resources. Currently, the software and hardware structure of this cipher utilize a complex logic operation to generate a sequence of random numbers called round constant and this causes the algorithm to slow down and record low throughput. To improve the speed and throughput of the original algorithm, the Fast Lightweight Encryption Device (FLED) has been proposed in this paper. The key size of the currently existing LED algorithm is in 64-bit & 128-bit but this article focused mainly on the 64-bit key (block size=64-bit). In the proposed FLED design, complex operations have been replaced by LFSR left feedback technology to make the algorithm perform more e

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Assessing the performance of commercial Agisoft PhotoScan software to deliver reliable data for accurate3D modelling
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3D models delivered from digital photogrammetric techniques have massively increased and developed to meet the requirements of many applications. The reliability of these models is basically dependent on the data processing cycle and the adopted tool solution in addition to data quality. Agisoft PhotoScan is a professional image-based 3D modelling software, which seeks to create orderly, precise n 3D content from fixed images. It works with arbitrary images those qualified in both controlled and uncontrolled conditions. Following the recommendations of many users all around the globe, Agisoft PhotoScan, has become an important source to generate precise 3D data for different applications. How reliable is this data for accurate 3D mo

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Modeling and Simulation for Performance Evaluation of Optical Quantum Channels in Quantum key Distribution Systems
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In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 prot

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Improve the Performance of PID Controller by Two Algorithms for Controlling the DC Servo Motor
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The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Tue Dec 13 2011
Journal Name
Iraqi Journal Of Laser
Evaluation of Low Level Laser Therapy Using Diode Laser in Enhancement of Episiotomy Wound Healing
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we studied the effect of low level laser therapy (LLLT) using diode laser with wavelength of (790-805) nm in promotion and enhancement of wound healing of episiotomy and to evaluate the analgesic effect of LLLT in reducing the pain sensation caused by the episiotomy wounds. Nineteen women with episiotomy wound were selected and divided into three groups; 1st group (group No.1: control group) given antibiotics without laser therapy, in the 2nd group (group No.2) the wounds were exposed to laser therapy (4 sessions, each session with energy density of 19.90 J /cm2 every other day ) and systemic antibiotics were prescribed for 1 week. In the 3rd group (group No.3) the wounds were exposed to laser therapy (4 sessions, the same as in the 2nd

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Mon Nov 09 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
The effect of different thermal treatments and pH on the stability of a glycyrrhizin which Product from the licorice plant, Glycyrrhiza glabra L: The effect of different thermal treatments and pH on the stability of a glycyrrhizin which Product from the licorice plant, Glycyrrhiza glabra L
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The plant licorice is considered important plants as nutritionally and medically and economically, as a rich in phytochemical, vitamins and minerals, and being widely available, Research indicated the presence of many nutrients such as (proteins, Carbohydrates, vitamins and minerals) as well as presence of Glycyrrhizin which responsible of sweet taste, that allowing the possibility to use it as natural intensity sweetener with few calories in Sweetening of many food. This research is aimed to study the Stability of Glycyrrhizin toward the various manufacturing conditions such as (thermal treatment, pH of foods and microwaves), so three factorial experiments was implemented to find out the Stability as following: 100C° - 121C° - Microwa

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