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Wyszukujesz frazę "Karam, Ekhlas H." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Design modified second order sliding mode controller based on ST algorithm for blood glucose regulation systems
Autorzy:
Karam, Ekhlas H.
Jadoo, Eman H.
Powiązania:
https://bibliotekanauki.pl/articles/117812.pdf
Data publikacji:
2020
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
Type I Diabetes
Second Order Sliding Mode Control
Chaotic Particle Swarm Optimization
BEM model
cukrzyca typu 1
kontrola trybu przesuwu drugiego rzędu
optymalizacja roju cząstek chaotycznych
model BEM
Opis:
The type1 of diabetes is a chronic situation characterized by abnormally high glucose levels in the blood. Persons with diabetes characterized by no insulin secretion in the pancreas (ß-cell) which also known as insulin-dependent diabetic Mellitus (IDDM). In order to keep the levels of glucose in blood near the normal ranges (70–110mg/dl), the diabetic patients needed to inject by external insulin from time to time. In this paper, a Modified Second Order Sliding Mode Controller (MSOSMC) has been developed to control the concentration of blood glucose levels under a dis-turbing meal. The parameters of the suggested design controller are optimized by using chaotic particle swarm optimization (CPSO) technique, the model which is used to represent the artificial pancreas is a minimal model for Bergman. The simulation was performed on a MATLAB/SIMULINK to verify the performance of the suggested controller. The results showed the effectiveness of the proposed MSOSMC in controlling the behavior of glu-cose deviation to a sudden rise in blood glucose.
Źródło:
Applied Computer Science; 2020, 16, 2; 18-31
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cancer growth treatment using immune linear quadratic regulator based on crow search optimization algorithm
Autorzy:
Hussein, Mohammed A.
Karam, Ekhlas H.
Habeeb, Rokaia S.
Powiązania:
https://bibliotekanauki.pl/articles/1837793.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
oncolytic virotherapy
feedback mechanism
crow search algorithm
Immune-LQR
wiroterapia onkolityczna
mechanizm sprzężenia zwrotnego
algorytm wyszukiwania w tłumie
Opis:
The rapid and uncontrollable cell division that spreads to surrounding tissues medically termed as malignant neoplasm, cancer is one of the most common diseases worldwide. The need for effective cancer treatment arises due to the increase in the number of cases and the anticipation of higher levels in the coming years. Oncolytic virotherapy is a promising technique that has shown encouraging results in several cases. Mathematical models of virotherapy have been widely developed, and one such model is the interaction between tumor cells and oncolytic virus. In this paper an artificially optimized Immune-Linear Quadratic Regulator (LQR) is introduced to improve the outcome of oncolytic virotherapy. The control strategy has been evaluated in silico on number of subjects. The crow search algorithm is used to tune immune and LQR parameters. The study is conducted on two subjects, S1 and S3, with LQR and Immune-LQR. The experimental results reveal a decrease in the number of tumor cells and remain in the treatment area from day ten onwards, this indicates the robustness of treatment strategies that can achieve tumor reduction regardless of the uncertainty in the biological parameters.
Źródło:
Applied Computer Science; 2021, 17, 2; 56-69
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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